diff --git a/README.md b/README.md index 12e4ef15..dba2ec44 100644 --- a/README.md +++ b/README.md @@ -27,10 +27,8 @@ To setup, ```sh setup_dependencies.sh cuda12``` -4) ``` pip install -r requirements.txt``` - -5) Run the Whisper-JAX pipeline. Currently, the repo can take a Youtube video and transcribes/summarizes it. +4) Run the Whisper-JAX pipeline. Currently, the repo can take a Youtube video and transcribes/summarizes it. ``` python3 whisjax.py "https://www.youtube.com/watch?v=ihf0S97oxuQ"``` diff --git a/Viz-experiments.ipynb b/Viz-experiments.ipynb index f52eb749..331c2061 100644 --- a/Viz-experiments.ipynb +++ b/Viz-experiments.ipynb @@ -18,7 +18,7 @@ }, { "cell_type": "code", - "execution_count": 24, + "execution_count": 18, "id": "edc584b2", "metadata": {}, "outputs": [ @@ -26,44 +26,54 @@ "name": "stderr", "output_type": "stream", "text": [ - "\u001b[32m2023-06-14 23:48:05.490\u001b[0m | \u001b[1mINFO \u001b[0m | \u001b[36mfile_util\u001b[0m:\u001b[36mdownload_files\u001b[0m:\u001b[36m36\u001b[0m - \u001b[1mDownloading file df.pkl\u001b[0m\n", - "\u001b[32m2023-06-14 23:48:07.270\u001b[0m | \u001b[1mINFO \u001b[0m | \u001b[36mfile_util\u001b[0m:\u001b[36mdownload_files\u001b[0m:\u001b[36m36\u001b[0m - \u001b[1mDownloading file mappings.pkl\u001b[0m\n", - "\u001b[32m2023-06-14 23:48:07.756\u001b[0m | \u001b[1mINFO \u001b[0m | \u001b[36mfile_util\u001b[0m:\u001b[36mdownload_files\u001b[0m:\u001b[36m36\u001b[0m - \u001b[1mDownloading file transcript_timestamps.txt\u001b[0m\n" + "\u001b[32m2023-06-23 15:01:36.558\u001b[0m | \u001b[1mINFO \u001b[0m | \u001b[36mfile_utilities\u001b[0m:\u001b[36mdownload_files\u001b[0m:\u001b[36m36\u001b[0m - \u001b[1mDownloading file df_06-23-2023_06:10:03.pkl\u001b[0m\n", + "\u001b[32m2023-06-23 15:01:38.450\u001b[0m | \u001b[1mINFO \u001b[0m | \u001b[36mfile_utilities\u001b[0m:\u001b[36mdownload_files\u001b[0m:\u001b[36m36\u001b[0m - \u001b[1mDownloading file mappings_06-23-2023_06:10:03.pkl\u001b[0m\n", + "\u001b[32m2023-06-23 15:01:39.179\u001b[0m | \u001b[1mINFO \u001b[0m | \u001b[36mfile_utilities\u001b[0m:\u001b[36mdownload_files\u001b[0m:\u001b[36m36\u001b[0m - \u001b[1mDownloading file transcript_with_timestamp_06-23-2023_06:10:03.txt\u001b[0m\n" ] } ], "source": [ - "from file_util import download_files\n", + "from file_utilities import download_files\n", "import pickle\n", "\n", "# Download files from S3 bucket. You can download multiple files at a time by passing a list of names\n", - "files_to_download = [\"df.pkl\", \"mappings.pkl\", 'transcript_timestamps.txt']\n", + "# files_to_download = [\"df.pkl\",\n", + "# \"mappings.pkl\",\n", + "# \"transcript_timestamps.txt\"]\n", + "\n", + "# set the timestamp \n", + "timestamp = \"06-23-2023_06:10:03\"\n", + "\n", + "# df,mappings,transcript_timestamps file names\n", + "df_file_name = \"df_\" + timestamp + \".pkl\"\n", + "mappings_file_name = \"mappings_\" + timestamp + \".pkl\"\n", + "transcript_file_name = \"transcript_with_timestamp_\" + timestamp + \".txt\"\n", + "\n", + "\n", + "files_to_download = [df_file_name,\n", + " mappings_file_name,\n", + " transcript_file_name] \n", "download_files(files_to_download)" ] }, { "cell_type": "code", - "execution_count": null, + "execution_count": 19, "id": "5027fe25", "metadata": {}, "outputs": [], "source": [ "# Download spacy model for the first time\n", - "!spacy download en_core_web_md\n" - ] - }, - { - "cell_type": "code", - "execution_count": 25, - "id": "a1fc2846", - "metadata": {}, - "outputs": [], - "source": [ + "import nltk\n", "import spacy\n", + "from nltk.corpus import stopwords\n", "\n", + "nltk.download('punkt', quiet=True)\n", + "nltk.download('stopwords', quiet=True)\n", "spaCy_model = \"en_core_web_md\"\n", "nlp = spacy.load(spaCy_model)\n", - "stopwords = nlp.Defaults.stop_words\n" + "spacy_stopwords = nlp.Defaults.stop_words\n", + "STOPWORDS = set(spacy_stopwords).union(set(stopwords.words('english')))" ] }, { @@ -82,6 +92,163 @@ "## Scatter plot of transcription with Topic modelling" ] }, + { + "cell_type": "code", + "execution_count": 23, + "id": "55a75dcf", + "metadata": {}, + "outputs": [ + { + "data": { + "text/html": [ + "
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timestamptextts_to_topic_mapping_top_1ts_to_topic_mapping_top_2
0(0.0, 12.36)this . Okay , yeah , so it looks like I am re...TAMFounders
1(12.36, 25.76)because Goku needs that for the audio plus the...FoundersTAM
2(25.76, 30.32)the rest of the team did . So I want to just ...FoundersAGENDA
3(30.32, 35.52)then we can ask questions or how do you want t...TAMFounders
4(35.52, 49.56)introduction . So what I , it all started wit...FoundersTAM
...............
554(3323.0, 3326.56)It 's crazy . But definitely with theFoundersTAM
555(3326.56, 3332.24)local models , we have n't found a way to work...FoundersTAM
556(3332.24, 3337.2)if you 'd have 90 minutes of audio to transfer...TAMFounders
557(3338.32, 3344.4)We actually have a preprocessor to resolve wha...FoundersTAM
558(3344.4, None)there 's still some struggles on the local mod...FoundersTAM
\n", + "

559 rows × 4 columns

\n", + "
" + ], + "text/plain": [ + " timestamp text \\\n", + "0 (0.0, 12.36) this . Okay , yeah , so it looks like I am re... \n", + "1 (12.36, 25.76) because Goku needs that for the audio plus the... \n", + "2 (25.76, 30.32) the rest of the team did . So I want to just ... \n", + "3 (30.32, 35.52) then we can ask questions or how do you want t... \n", + "4 (35.52, 49.56) introduction . So what I , it all started wit... \n", + ".. ... ... \n", + "554 (3323.0, 3326.56) It 's crazy . But definitely with the \n", + "555 (3326.56, 3332.24) local models , we have n't found a way to work... \n", + "556 (3332.24, 3337.2) if you 'd have 90 minutes of audio to transfer... \n", + "557 (3338.32, 3344.4) We actually have a preprocessor to resolve wha... \n", + "558 (3344.4, None) there 's still some struggles on the local mod... \n", + "\n", + " ts_to_topic_mapping_top_1 ts_to_topic_mapping_top_2 \n", + "0 TAM Founders \n", + "1 Founders TAM \n", + "2 Founders AGENDA \n", + "3 TAM Founders \n", + "4 Founders TAM \n", + ".. ... ... \n", + "554 Founders TAM \n", + "555 Founders TAM \n", + "556 TAM Founders \n", + "557 Founders TAM \n", + "558 Founders TAM \n", + "\n", + "[559 rows x 4 columns]" + ] + }, + "execution_count": 23, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "\n", + "df = pd.read_pickle(df_file_name)\n", + "df" + ] + }, { "cell_type": "markdown", "id": "a795137e", @@ -92,7 +259,7 @@ }, { "cell_type": "code", - "execution_count": 27, + "execution_count": 25, "id": "43e01074", "metadata": {}, "outputs": [], @@ -100,14 +267,14 @@ "import pandas as pd\n", "import scattertext as st\n", "\n", - "df = pd.read_pickle(\"df.pkl\")\n", + "df = pd.read_pickle(df_file_name)\n", "\n", "def plot_topic_modelling_and_word_to_sentence_search(df, cat_1, cat_1_name, cat_2_name):\n", " df = df.assign(parse=lambda df: df.text.apply(st.whitespace_nlp_with_sentences))\n", "\n", " corpus = st.CorpusFromParsedDocuments(\n", " df, category_col='ts_to_topic_mapping_top_1', parsed_col='parse'\n", - " ).build().get_unigram_corpus().remove_terms(stopwords, ignore_absences=True).compact(st.AssociationCompactor(2000))\n", + " ).build().get_unigram_corpus().remove_terms(STOPWORDS, ignore_absences=True).compact(st.AssociationCompactor(2000))\n", " \n", " html = st.produce_scattertext_explorer(\n", " corpus,\n", @@ -116,12 +283,12 @@ " width_in_pixels=1000,\n", " transform=st.Scalers.dense_rank\n", " )\n", - " open('./demo_compact.html', 'w').write(html)\n", + " open('./new_viz_' + timestamp + '.html', 'w').write(html)\n", "\n", "plot_topic_modelling_and_word_to_sentence_search(df,\n", - " cat_1=\"Workforce\",\n", - " cat_1_name=\"Workforce\",\n", - " cat_2_name=\"Enablement\")\n", + " cat_1=\"Founders\",\n", + " cat_1_name=\"Founders\",\n", + " cat_2_name=\"TAM\")\n", "\n", "# once you are done, check the generated HTML file\n" ] @@ -144,12 +311,12 @@ }, { "cell_type": "code", - "execution_count": 34, + "execution_count": 26, "id": "7cdcd66f", "metadata": {}, "outputs": [], "source": [ - "mappings = pickle.load(open(\"mappings.pkl\", \"rb\"))\n", + "mappings = pickle.load(open(mappings_file_name, \"rb\"))\n", "timestamp_to_topic_first_match = mappings[0]\n", "timestamp_to_topic_second_match = mappings[1]\n", "topic_to_timestamp_first_match = mappings[2]\n", @@ -158,13 +325,13 @@ }, { "cell_type": "code", - "execution_count": 35, + "execution_count": 27, "id": "11221022", "metadata": {}, "outputs": [ { "data": { - 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\n", 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\n", 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\n", 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3216.72),\n", + " (3227.0, 3231.0),\n", + " (3231.0, 3234.0),\n", + " (3240.0, 3241.0),\n", + " (3244.56, 3249.92),\n", + " (3255.88, 3257.44),\n", + " (3257.44, 3261.24),\n", + " (3261.24, 3268.4),\n", + " (3268.4, 3275.28),\n", + " (3323.0, 3326.56),\n", + " (3326.56, 3332.24),\n", + " (3338.32, 3344.4),\n", + " (3344.4, None)]" ] }, - "execution_count": 37, + "execution_count": 28, "metadata": {}, "output_type": "execute_result" } @@ -372,7 +753,7 @@ "def retrieve_time_segments(topic):\n", " return topic_to_timestamp_first_match[topic]\n", "\n", - "search_topic = \"Enablement\"\n", + "search_topic = \"Founders\"\n", "print(\"Timelines where \" + search_topic + \" was covered : \")\n", "time_segments_of_interest = retrieve_time_segments(topic=search_topic)\n", "time_segments_of_interest" @@ -388,7 +769,7 @@ }, { "cell_type": "code", - "execution_count": 38, + "execution_count": 31, "id": "5dc2014f", "metadata": {}, "outputs": [], @@ -396,10 +777,10 @@ "import json\n", "import ast\n", "\n", - "time_segments_of_interest = retrieve_time_segments(\"Enablement\")\n", + "time_segments_of_interest = retrieve_time_segments(\"Founders\")\n", "\n", "ts_transcript = {}\n", - "with open(\"transcript_timestamps.txt\", \"r\") as f:\n", + "with open(transcript_file_name, \"r\") as f:\n", " ts_transcript = f.read()\n", "ts_transcript = ast.literal_eval(ts_transcript)\n", "\n", @@ -411,17 +792,17 @@ }, { "cell_type": "code", - "execution_count": 39, + "execution_count": 32, "id": "caeff7f1", "metadata": {}, "outputs": [ { "data": { "text/plain": [ - "\" So everything's going well so far. I'm going to join us. This is where you keep this low key. Very casual. Absolutely. All right. Well, thank you all for being here. We're very honored that you came to join us for this conversation. We are going to spend a little bit of time. I know it was written up, right? But thinking about how you actually grow and retain your employees, we know that there's a war on talent, especially in the cyberspace right now, right? Everybody's trying to get everybody in the door. Type lines are a little bit dry, a little bit hard to find. It's a tricky scenario. What we want to do if you allow us for this session is to almost park that call to the site. We're just going to spend just leaving for the moment. We're just going to put that aside. And instead, what we're going to focus on, or the employees that you actually have on board, already. We know that the hiring piece is complex. It requires dollars and HR and a whole bunch of stuff. That's that. We're going to focus on the rest, which is your workforce today. How do you grow them? How do you retain them? And in doing so, you actually find the bill become more effective and efficient and committed to your organization. So that then they'll go ahead and become more effective and committed to your organization. So that then they'll go ahead and become more effective and committed to your organization. So that then they'll go ahead and become more effective and committed to your organization. So that then they'll go ahead and become more effective and committed to your organization. So that then they'll go ahead and become more effective and committed to your organization. So that then they'll go ahead and become more effective and committed to your organization. So that then they'll go ahead and become more effective and committed to your organization. So that then they'll go ahead and become more effective and committed to your organization. So that then they'll go ahead and become more effective and committed to your organization. So that then they'll go ahead and become more effective and committed to your organization. So that then they'll go ahead and become more effective and committed to your organization. So that then they'll go ahead and become more effective and committed to your organization. So that then they'll go ahead and become more effective and committed to your organization. So that then they'll go ahead and become more effective and committed to your organization. So that then they'll go ahead and become more effective and committed to your organization. So that then they'll go ahead and become more effective and committed to your organization. So that then they'll go ahead and become more effective and committed to your organization. So that then they'll go ahead and become more effective and committed to your organization. So that then they'll go ahead and become more effective and committed to your organization. So that then they'll go the bell become more effective and efficient and committed to your organization. So then they'll go ahead and become random ambassadors for youis. I am a senior manager in the WIC capital practice. I'm focus on organizational transformation. What does that mean? That's where we quite all of our organizational design work. So how offices are aligned on the work chart and how information and decisions flow. In addition, it's where we hold our culture and our communications work. I've spent my career at Lloyd and beyond previously focused on culture and communications and employee and workforce programs and how you encourage the engagement and employee experience is the best thing to do. I've done that in a couple of clients' faces including the Federal Space, State Space, Global Space, including with some cyber agencies as well. But that'll answer my question. Thanks, Seize. You're going to have to be in the everyone. I'm part of the task. And I'm also a senior manager, absolutely. And I lead work for six periods for the government and public services practice at our firm. I want to forefront of workforce experience issues. For commercial cities, state, and federal clients focusing on training, attracting talent, recruiting, retention, and really today what we want to do is share some best practices, tools, what we've seen from other clients and help you. you some ideas about how to become an employer and choice, and how to retain the attract, high-performing cyber-talented. So, a little divergent? Before we do, I just want to give one caveat. Because it's day two of the conference now that the feedback cyber-fert, a while. I would say Mar and I both want to copy up the neater of us, or going to be cyber experts, especially in the room of this caliber. Yeah, right? We do this with cyraclients, but we also use with other clients. And so our invitation to you is to take what we're going to share here and think about how that applies to your day-to-day organization. So we kind of did this a little bit to stretch that thinking outside of just this formal cyber realm and bring you some ideas of what we're seeing from outside. That works. Okay. Great. So, actually, we define work for six periods, holistically, as there's some of our workers lived experience at work and how they feel about their organization. And so, really, this is shaped by eight key dimensions that impact worker experience overall. So we'll start by walking through each of these. So really this framework is backed by research as well as testing solutions with both our commercial as well as our government clients and we start with the people I work with. And this is really support and recognition for managers and you know who you interact with day to day. That's all in the side. It has one of the top five factors or talent retention. for the technology that I use. So that's very much about frustration, free technology. So are you having to do work around? So you're having to call IT or spend a lot of your day trying to figure out how to actually use this technology to do your job. And are there ways to use technology to improve collaboration, coordination and communication in a way that you're able to do your work more efficiently. The next little focus on is the places I do work, which is really focusing on the flexibility of the physical workspace and how that improves employee productivity, increases job satisfaction, and lowers overall workplace stress. Another one that we focus on is a sensible longing and or theness. That an organization creates. So that's very much about increasing your job performance. I think we've cited that it can lead to a 56% increase in job performance and a 50% reduction in turnover risk. And the work I do. I think this is particularly important to cyber employees where a lot of government employees are driven by the mission of the work that they're doing. And so connecting work to meaningful experiences and reiterating that's fulfilling and contributes to something bigger themselves is a great way to motivate and keep employees, that increases workers satisfaction. And then another one is really focusing on the mission. So identifying, you know, the organizations purpose and connecting it to their own personal values, as well as the mission of the organization. And finally, education. So this is really about higher form of organizations. And the fact that we have a lot of opportunities, we have a lot of opportunities to do that. And we have a lot of opportunities to do that. And we have a lot of opportunities to do that. And we have a lot of opportunities to do that. And we have a lot of opportunities to do that. And we have a lot of opportunities to do that. And we have a lot of opportunities to do that. And we have a lot of opportunities to do that. And we have a lot of opportunities to do that. And we have a lot of opportunities to do that. And we have a lot of opportunities to do that. And we have a lot of opportunities to do that. And we have a lot of opportunities to do that. And we have a lot of opportunities to do that. And we have a lot of opportunities to do that. And we have a lot of opportunities to do that. And we have a lot of opportunities to do that. And we have a lot of opportunities to do that. And we have a lot of opportunities to do that. And we have a lot of opportunities to do that. And we have a lot of opportunities to do that. And we have a lot of opportunities to do that. And we have a lot of opportunities to do that. And we have a lot of opportunities to do that. And we have a lot of opportunities to do that. And we have a lot of opportunities to do that. And we have a lot of opportunities to do that. And we have a lot of opportunities to do that. And we have a lot of opportunities to do that. And we have a lot of opportunities to do that. And we have a lot of opportunities to do that. And we have a lot the mission of the organization. And finally, education. So this is really about high-performing organizations and the fact that 30 times, 37 times more likely, workers are going to be able to achieve their local roles and stay within organization if they have the proper training and support and experiences to help them get there. So really when thinking about workforce experience, organizations, you know, often are sure where to start or what elements impact their employees. So this framework is really what we use as a starting point to help contributors that we've seen in our experience to employees really engage and motivated, which has directly contributed to retaining a attracting talent. So with that we are going to move on to the next slide. So just our off cybersecurity employees we know are experiencing disruption unlike ever before. And so just to a great day's discussion, we first went to start by walking through how one agency has approached the issue and used work force experience to address it. So a large federal agency of the Agile Cyber Security Priorities had long-suning workforce issues, you know, lots of attrition, tough time attracting the right talent for the roles that they needed. Probably a little bit about what you all are seeing. So there are a couple of stats up on this slide. I don't think they're going to surprise anybody, but I just want to call them out, because I think they're an important framing for what we are seeing in this library industry, Can you see it? No, I don't know. Okay, I'll go through a learn after reading for you. Yeah. And they were asking questions about the general cybersecurity environment, but in addition, some things came out around the workforce. So when those CISO's were asked about how they can support emerging threats and what their biggest challenges, number one, they said legacy infrastructure and solutions, number two, they said workforce. The number two thing, holding these state CISO's back from responding to the threats that are coming is the workforce. That's a pretty big issue. And the number two thing, the number two thing, the number two thing, holding these state CISO's back from responding to the threats that are coming is the workforce. That's a pretty big issue. And the number two thing, the number two thing, the number two thing, the number two thing, the number two thing, the number two thing, the number two thing, the number two thing, the number two thing, the number two thing, the number two thing, the number two thing, the number two thing, the number two thing, the number two thing, the number two thing, the number two thing, the number two thing, the number two thing, the number two thing, the number two thing, the number two thing, the number two thing, the number two thing, the number two thing, the number two thing, the number two thing, the number two thing, the number two thing, the number two thing, the number two thing, the number two thing, the number two thing, the number two thing, the number two thing, the number two thing, the number two thing, the number two thing, the number two thing, the number two thing, the number two thing, the number two thing, the number two thing, the number two thing, the number two thing, the number two thing, the number two thing, the number two thing, the number two thing, the number two thing, the number two thing, the number two thing, the number two thing, the number two thing, the number two thing, the number two thing, the number two thing, holding these state-sea-sodes back from responding to the threats that are coming, is the workforce. That's a pretty big issue. In addition, 62% out-to-thirds reported that their staff have a gap in competencies. Don't have the skills to do the job. Another pretty big issue when you step back and look at it. When we talk about the belonging piece that Mara just talked about and shared, 23% with the respondents didn't know if their organization has established DEI leadership positions. So is there someone in the organization really focused on that inclusion piece and bringing all of your workforce along? And only 25% reported offering remote work options, which I know is tricky in the cyberspace. When you think about the sock and everything else, but it is there are ways to do it with at least parts of the workforce. And we know that that's the same thing. And we know that that's the same thing. And we know that that's the same thing. And we know that that's the same thing. And we know that that's the same thing. And we know that that's the same thing. 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And we know that that's the same thing. And we know that that's the same thing. And I know is tricky in the cyberspace. When you think about the sock and everything else, but it is there are ways to do it with at least parts of the workforce. And we know that that's super important to the millennials and slunder-reppers any groups. Remote work has certainly been a topic since the pandemic, right? I see people nodding. It's just on everybody's tongue, it's front of mind. So how do you make that work? You know, addition to all of this, I think what's really important to know, right? Is that cyber threats have not produced in any way? So there's one stat that says that as a result of COVID-19, it's been linked to a 238% increase in cyber crime. So the numbers are going up the need continues and the resourcing and the workforce, maybe as a little bit lagging behind. In addition to this in a cyberspace, we're also seeing some pretty big macro trends in workforce space in general that are contributing to some of the challenges going on today. And these also probably won't surprise you. Number one, exhaustion. So this is where that burnout topic that some of you people are talking about is showing up. And in cyber agencies, we have frontline workers, right? There's a 24-7 operation. And so you're going to have this burnout challenge unfortunately. This is also contributed by working from home in some ways and that blurring of that work life home life when it ended the day happens if it happens and whose days on their laptop all night working. In addition, between 2021 and 2022, the number of meetings we all experience increased 280 percent. So you're getting your Zoom fatigue, your Teams fatigue, right? Does that Why does all this matter? Because we know that losing employees is costly. So if you can get it right on the front end and really have that workforce experience be positive and keep your people it's going to pay off dividends in the actual. I'm going to pass it back to Mara who's going to tie this back to that model for us. that improves the business and talent outcomes. And so, it's investing in work more experience is a single best way that organizations can minimize workforce disruption in the short term. I'm going to get ahead of future work. How do we do that? And so in this next section we're going to focus on how cyber employers can win at workforce experience. So based on a 2022 state CIO, mass CO study that included 51 participants, it was identified that the following areas were some of the top priorities around how to improve workforce experience. work options as particularly important 8% focus on flexible work schedules and how work affects their life 35% focus on how I grow as a human so focusing on sure that the workforce is able to meet the needs of the modern IT to man's. And so with this, Suzy is going to walk us through a deeper dive of the different options on how to address these results with this actually might look like in practice. Great. Thank you, Mara. So again, just to take it from the top, right? You know that the talent pipeline is tough. We know that we're recruiting processes challenging. I think a little deeper into some of these things. We're going to walk through a couple of activities, programs, initiatives, ideas, just to hopefully give you something to walk away with today that you can take back to your organization and implement. And the idea behind these is you can implement them tomorrow. You don't need to get into an IT backlog of some system build. You don't need to go to HR and say, I need, you know, millions of dollars to hire people and fill the gaps. These are things that you can do with your current workforce in place today to improve that workforce experience. So, starting with how I grow with a human and again 35% of the CIOs said that this was one of the most important things. A couple of ideas here for things that can be done and things that we've seen these accessible elsewhere. Number one, integrating training into the day-to-day. This is not about sending it employee off to go take a training, get a certification, step out of the workplace, and come back. We know that most adult learners prefer experiential learning. And so the way to do that is a apprenticeship, mentorship, shadowing, rotational programs, lunch and learns, informal training opportunities, action, after action reports where you can also around and talk about what did we do well, what didn't we do, what are we going to do differently. And some of this also is just documenting what it is you do. So setting up some of those SOPs so that you can pass those over to somebody and say, well this is the best way to do it. Here's a lesson's learned. Identifying opportunities for employees to use their strengths daily. When we talk about strengths, we don't just mean what am I good at. What we mean by strengths is what gives me individually energy. What energizes me? What excites me? And so I may be very good at data analytics, but that doesn't mean that that's my passion. I may actually prefer competing teams or communications or something like that. And so checking in with your teams about what is it that they each person enjoys most and trying to align them to that work. Studies have shown that if you align people to their strengths, again, the things that energize them, they will actually outperform, and do way better than if you give them a challenge task or activity that then they have to sort of overcome and be able to accomplish. We are good when we're playing to our strengths. So it doesn't mean that in a play you can only do their strength all day and be happy, but try to find ways for them to incorporate their strengths into the day to day as much as possible. And then another thing that tends to be useful is stepping back and building looking at career pathways. So how are you going to grow people from level to level, from ability to ability? Is anybody here familiar with the nice framework? Come on, Nick. if you haven't seen an highly recommend going onto the website. They have work titles, they have job descriptions, they have competencies, they have skills, knowledge, experiences, and you can stack roles so you can say, okay, if I'm an IT leadership management position today, and I want to become a data analyst, and they will help you kind of, they map that path a little bit for you with the overlap between those two roles for example and then some of the case this knowledge skills and abilities to go get from one to the other. So a very very useful tool used by a lot of cyber agencies and organizations highly highly highly highly recommend using it or at least checking an out and seeing if there's anything useful for you there. But really looking at where are my people going and how to like grow them because we know also that one of the most important things that we have to do is to make sure that we have a lot of information about the data that we have to do with the data and that we have to do with the data that we have to do with the data that we have to do with the data that we have to do with the data that we have to do with the data that we have to do with the data that we have to do with the data that we have to do with the data that we have to do with the data that we have to do with the data that we have to do with the data that we have to do with the data that we have to do with the data that we have to do with the data that're doing it. And we know that we're doing it. And we know that we're doing it. And we know that we're doing it. And we know that we're doing it. And we know that we're doing it. And we know that we're doing it. And we know that we're doing it. And we know that we're doing it. And we know that we're doing it. And we know that we're doing it. And we know that we're doing it. And we know that we're doing it. And we know that we're doing it. And we know that we're doing it. And we know that we're doing it. And we know that we're doing it. And we know that we're doing it. And we know that we're doing it. And we know that we're doing it. And we know that we're doing it. And we know that we're doing it. And we know that we're doing it. And we know that we're doing it. And we know that we're doing it. And we know that we're doing it. And we know that we're doing it. And we know that we're doing it environment. I know the sock is what it is. We know that piece. But there are conversations still to be having around work location. What we have found is most successful is when organizations really focus in on work location. In alignment to your desires, your goals, your strategy. There are some things that working remote are great for. running into somebody, you know, by the water cooler and finding out that we're doing similar things, and we can train notess actually Mara and I just did that and I said oh send me that if you could because I want to see that right? So designing intentionally for what work can be done in person, what work can be done remotely, maybe it's part and part. Maybe there's a single initiative or project where you can send people to go home and work remotely and then come back and they're still feeling like they're getting a taste of that opportunity as they're normally meeting to be on site. So really being smart and intentional and purposeful about how you design that. Looking at the digital communications and information sharing. So a lot of us have moved on to teams and Slack and Zoom and these digital tools. Are you really using them for their maximum capability to support your organization? Is there license to and bringing that goodness to your organization to help your people work even better? And then the third one there is forced to connectivity and networking especially in a hybrid or remote environment. We know that happiness at work and elsewhere So how are you forcing some of that social connection? and saying, hey, how is everybody's weekend? Or what are you doing this weekend? Or tell me something funny? Or if you were going to be a office supply, what would you be? Whatever it may be, right? But finding a way to sort of force a little door opening and having people build that connection. And then the well being piece. And so I shared with you about the exhaustion, you know, and the burnout rates and all that earlier. A lot of organizations, especially since during and since the pandemic, have stood up well being activities. They're not necessarily aligned to a situation where they're not going to be able to do that. And so I'm going to be able to do that. And I'm going to be able to do that. And I'm going to be able to do that. And I'm going to be able to do that. And I'm going to be able to do that. And I'm going to be able to do that. And I'm going to be able to do that. And I'm going to be able to do that. And I'm going to be able to do that. And I'm going to do that. And I'm going to be able to do that. And I'm going to do that. And I'm going to do that. And I'm going to do that. And then remember that it has a lot of opportunities to do that. And then remember that it has a lot of opportunities to do that. And then remember that it has a lot of opportunities to do that. And then remember that it has a lot of opportunities to do that. And then remember that it has a lot of opportunities to do that. And then remember that it has a lot of opportunities to do that. And then remember that it has a lot of opportunities to do that. And then remember that it has a lot of opportunities to do that. And then remember that it has a lot of opportunities to do that. And then remember that it has a lot of opportunities to do that. And then remember that it has a lot of opportunities to do that. And then remember that it has a lot of opportunities to do that. And then remember that it has a lot of opportunities to do that. And then remember that it has a lot of opportunities to do that. And then remember that it has a lot of opportunities to do that. And then remember that it has a lot of opportunities to do that. And then remember that it has a lot of opportunities to do that. And then remember that it has a lot of opportunities to do that. And then remember that. So it's not just sort of a scatter plot of activities, but there's sort of intentional and organized aligning back to those goals that you have. And then, remember that impact of that and adjust as needed. And if you're engaging your workforce correctly, then you'll have lots of data points about what's working and what's not in order to make those adjustments. make those adjustments. Started on this a little bit, but again, thinking creatively, not just about remote work, but how shift work is scheduled. So a lot of the conversation around workforce and economic development is around people who may be to be taking their child care duties at home while still trying to get into the workforce. What is it that you can do to maybe look at four hour shifts or six hour shifts different than your typical shifts to bring in more people in diversity, and also alleviate some of the burnout and pressure that's happening for the workforce in place today. There are a bunch of apps that focus on this. A lot of them are focusing in the health care space of the transportation frontline workers space, but they could easily be leveraged over into the cyberspace as well. And then the third one here conducting a culture assessment. A lot of organizations assume that culture sort of just happens and it doesn't. It's important to be intentional about culture and what do we mean when we talk about culture, right? Because we all sort of live in it all the time, but what is that? When we talk about culture, what we talk about are the intangibles, your beliefs and your values as an organization. Are we more individually individualistic, the ability to talk about culture, what we talk about, what we talk about, what we talk about, what we talk about, what we talk about, what we talk about, what we talk about, what we talk about, what we talk about, what we talk about, what we talk about, what we talk about, what we talk about, what we talk about, what we talk about, what we talk about, what we talk about, what we talk about, what we talk about, what we talk about, what we talk about, what we talk about, what we talk about, what we talk about, what we talk about, what we talk about, what we talk about, what we talk about, what we talk about, what we talk about, what we talk about, what we talk about, what we talk about, what we talk about, what we talk about, what we talk about, what we talk about, what we talk about, what we talk about, what we talk about, what we talk about, what we talk about, what we talk about, what we talk about, what we talk about, what we talk about, what we talk about, what we talk about, what we talk about, what we talk about, what we talk about, what we talk about, what we talk about, what we talk about, what we talk about, what we talk about, what we talk about, what we talk about, what we talk about, what we talk about, what we talk about, what we talk about, what we talk about culture, what we talk about are the intangibles, your beliefs and your values as an organization. Are we more individually individualistic, focused or are we more collaborative? Are we more risk of first? Or are we more innovative and risk takers? Are we more internally focused or do we have external customers that we've really organized around? And so when you do a cultural assessment, you look at where you are today versus where you want your organization to be and what are the steps to get from a to the other. And so when you do a cultural assessment, you look at where you are today versus where you want your organization to be and what are the steps to get from a to the other. And so when you do a cultural assessment, you look at where you are today versus where you want your organization to be and what are the steps to get from a to the other. And so when you do a cultural assessment, you look at where you are today versus where you want your organization to be and what are the steps to get from a to the other. And so when you do a cultural assessment, you look at where you are today versus where you want your organization to be. And so when you do a cultural assessment, you look at where you are today versus where you want your organization to be. And what are the steps to get from a to the other. And so when you do a cultural assessment, you look at where you are today versus where you want your organization to be. And what are the steps to get from a to the other. And so when you do a, what are the steps to get from a to the other. And so when you do a, what are the steps to get from a, what are the steps to get from a, what are the steps to get from a, what are the steps to get from a, what are the steps to get from a, what are the steps to get from a, what are the steps to get from a, what are the steps to get from a, where you want your organization to be, and what are the steps to get from A to Z? And how do you do that in a way that then filters and flows through your entire organization? So that by the time you get to performance reviews or your next strategic planning cycle, we're standing up a new program or redesigning your organization, there is an friction with what it is you really want from your employees and what you're trying to achieve as an organization and how you're getting there. So cultural assessment, well, it seems like a sort of unnecessary. It's actually very effective and super supportive of your articles. Okay, I've talked a lot. Lots of ideas. Hopefully, good menu for you to pick at least something from a fithesical. I'm going to pass it back to Mara to kind of bring it all together for us. Thank you, Sissy. So, how can employers win at work for six variants? So, practically speaking, they keep it implementing a successful work for six variants. Really starts with understanding what your workforce wants. That can be through a survey or focus groups doing doing user research, but really putting their voice at the center of these initiatives. And then working to prioritize which ones within your organization and help you achieve your overall business objectives. So we're going to walk through our perspective on what it means to really bring work for six periods to an organization. So starting with employers need to think about beyond employment engagement. And so what we mean by this is it's not just one data point, our employees engaged, you know, how I retained my staffer did I recruit an attractive, you know, this number of individuals? It's beyond that and a combination of those aid characteristics that really helps to retain employees and attract the right talent and enhance the overall workforce experience. So an example of that is, you know, looking at physical workspace. So, you know, do they are they able to do their work remotely? In some cases, as Susie mentioned, they do they have everything they need in the office in order to be productive, to get things done in terms of head-stallam work versus hue collaboration, culture, do they, are they recognized for their work? It was great as a hundred dollar gift card is for a great job and something. It in a lot of cases what we found is it's equally just as advantageous to how we manage our reach out and saying thank you so much. You did a great job and acknowledge that. And that's why we know what can motivate and keep employees engaged. And another area is technology. I think we mentioned you know it's a way to help collaborate, work remotely, but it can also be an impediment to when technology isn't easily accessible within organization. The second one that we really focus on and this goes back to its Susie set of Fiesta's and also what I mentioned around the voice of the workforce. And so, incorporating that throughout the design is incredibly important. One of the first things that we often do is pull survey of a particular group to understand what they really hear about. What are their preferences? If they had, it's not just, I want more money, but but rather if you had a choice between a little bit more flexibility in your work schedule versus you know increased recognition, you know, where do they release stand in terms of what should actually get prioritized? a workforce once a year through an annual HR survey of how do you really feel like you know what leadership considerations should we implement or you know how can we enhance the performance management process? It's really on an ongoing basis and even in in an informal way, you as leaders and managers of teams asking your teams, you know, what they care about, what their frustrated about, what their preferences are, and taking small steps where you can to try to incorporate that into how they work. And you know, sometimes it's challenging to do organization-wide changes that take a lot of funding and investment and capabilities. So often, you know, you know, you can do a lot of things. And you know, you can do a lot of things. And you know, you can do a lot of things. And you know, you can do a lot of things. And you know, you can do a lot of things. And you know, you can do a lot of things. And you know, you can do a lot of things. And you know, you can do a lot of things. And you know, you can do a lot of things. And you know, you can do a lot of things. And you know, you can do a lot of things. And you know, you can do a lot of things. And you know, you can do a lot of things. And you know, you can do a lot of things. And you know, you can do a lot of things. And you know, you can do a lot of things. And you know, you can do a lot of things. And you know, you can do a lot of things. And you know, you can do a lot of things. And you know, you can do a lot of things. And you know, you can do a lot of things. And you know, you can do a lot of things. And you know, you can do a lot of things. And you know, you can do a lot of things. And you know, you can do a lot of things. And you know, you can do a lot of things. And you know, you can do a lot of things. And you know, you can do a lot of things. And you know, sometimes it's challenging to do organization why changes that take a lot of funding, investment, So oftentimes, a way to do that is through, you know, more informal touch points on individual teams that you're leading. We found that that's a concept that's a quick way to be able workplace technology and we've talked about this a little bit and I think really with this it's how do you boost productivity? Workers want to do a great job. They're they're at the perform well. They, you know, are often very mission-driven. They want to grow their careers and they want to try to be as efficient as they can in their job. And so really looking at how this can give you a major accelerator based on how you work. Do you want an hands collaboration? Do you want to try to create more opportunities for a hybrid or remote work? And, you know, through technology, that can really enhance and accelerate a lot of those activities. And so with all of these four areas combined, this is what we've seen across, you know, four-Jet 500 companies, federal agencies, city, city, agencies as well, as kind of the key characteristics and commonalities amongst the most effective and fully engagement and workforce experience programs. And just to kind of round things out with this globe is, you know, if workforce experience, I recognize, you know, can seem kind of fluffy and like, oh, that's a nice to have. But our premise is that your workforce is the most important asset in your organization. And if they are in the most important asset, you really want to invest in them. To, you know, day to day, be the driver of change in, you know, be the lower productivity. We've just found that, you know, by investing in this, you know, day to day be the driver of change in, you know, be the alert productivity. We've just found that, you know, by investing in this and putting the workforce as, you know, the center part of what you invest in as an organization in leaders. It's not only about retention talent, you know, the cyber workforce crisis, but people want to do work well and they're able to get more done and achieve more without you, you know, directly supervising and micro managing or looking at everything because they just genuinely want to work for you and are able to be more productive overall in that way. So with that, that is our presentation for today. I hope there's a little bit of, you know, the landscape of the cyber workforce with some practical tips that you can take away for how to just think about, you know, improving the overall workforce experience and investing in your employees. So with this, you know, we know that all of you are in the trenches every day. You're facing this, you're living this. And we are just interested to hear from you. And we are interested to hear from you. And we are interested to hear from you. And we are interested to hear from you. And we are interested to hear from you. And we are interested to hear from you. And we are interested to hear from you. And we are interested to hear from you. And we are interested to hear from you. And we are interested to hear from you. And we are interested to hear from you. And we are interested to hear from you. And we are interested to hear from you. And we are interested to hear from you. And we are interested to hear from you. And we are interested to hear from you. And we are interested to hear from you. And we are interested to hear from you more excited. I'm going to be a little bit more excited. I'm going to be a little bit more excited. I'm going to be a little bit more excited. I'm going to be a little bit more excited. I'm going to be a little bit more excited. I'm going to be a little bit more excited. I'm going to be a little bit more excited. I'm going to be a little bit more excited. I'm going to be a little bit more excited. I'm going to be a little bit more excited. I'm going to be a little bit more excited. I'm going to be a little bit more excited. I'm going to be a little bit more excited. I'm going to be a little bit more excited. I'm going to be a little bit more excited. I'm going to be a little bit more excited. I'm going to be a little bit more excited. I'm going to be a little bit more excited. I'm going to be a little bit more excited. I'm going to be a little bit more excited. I'm going to be a little bit more excited. I'm going to be a little bit more excited. I'm going get someone. Sorry. Don't be shy. So yeah, I'm so worried. How is something or what hasn't worked well, you know, that's something that's easier to start with too. But we'd love to just hear from all of you because I think, you know, how we've aggregated a lot of these best practices and what we've come with, it is by, you know, hearing other experiences from other organizations. And so, one of the best and most effective things, I feel like I take away from conferences often is hearing from many peers and what they're facing and, you know, let, you know, similarly, I could bring back to what I'm leading. What about you? Oh, I see him back there. I'm going to the water. I'm going to the water. I'm going to the water. I'm going to the water. I'm going to the water. I'm going to the water. I'm going to the water. I'm going to the water. I'm going to the water. I'm going to the water. 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I'm going to the water. I'm going to the water. I'm going to the water. I'm going to the water. I'm going to the water. I'm going to the water. I'm going to the water. I'm going to the water. I'm going to the water. I'm going to the water. I Thank you.\"" + "\"because Goku needs that for the audio plus the transcript plus the timestamps . So cool . Okay , so we can have our discussion as planned about ontology prompt . So JDC , I just wanted to learn about it and I think the rest of the team did . So I want to just start off , maybe you want to give us some context and introduction . So what I , it all started with the demo from Palantir. , as you know , they were able to make this AIP thing where they were such a powerful thing perhaps because they use an ontology . So it means that they have a definition of entities and actions that they can take . So then they control this to an LLM . So I started exploring with that with Jamo . in our hierarchical way using just like texts . And it kind of works . So in the end , I decided that one good pattern operations , mutations and queries over certain entities . So I assume that many of the LLMs have seen a lot of this data and know how to operate . So people from OpenAI and many companies So that 's how I started . So one of the problem domains that we could map to this , it 's CP because it 's some actions that you need to take . So that 's basically the system I end up developing . But that has some challenges . So the first thing is that , let me share the screen . And I can take you over . It 's amazing that Corey , Michal , and John are attending , because I 'm reaching to the point that I would love to have more ideas . Can you see the screen ? to you independently , just very late for him today . So I started by like mocking these kind of entities that could work with Zibi . So we have like employees , candidates . I just took a look at out of the comments that we support right now , reminders , and then put together this GraphQL thing . Yeah . Right now I see the whereby window . Is that what you 're showing ? Oh , sorry . No . Let me see . Maybe I 'm just sharing one , not the whole screen . Okay . I think this will solve it . that we have for many purposes , like requesting vacations and some other things . So there are some entities that are employees . I just like mocked some of them . just mocked up . Get reminder . This was the first thing . There is the vacations input , create reminder , and some mutation . So as you can see , this is part of the first test that I did . So let me show you here how this can work . So let 's say in the first day of July , I 'm trying to , sorry , I was in the middle of some page here . Oh , my God . It 's always show up . Yeah , yeah . I 'm refactoring like heavily this , but you see , it does work very well . So wait , let me change the strategy here . Let me see another example . Okay . So let 's say vacations . Because I 've been experimenting a lot . Just want to show you one related with vacation . Well . Let me see if it can work this way . I have many modes of operation . It behaves very good for this kind of . So it creates vacations , it fills all the things here . So this can basically be adapted to any CLI . GraphQL pretty well . command line interface for many things as long as you can describe the things like this . And this is a very flexible pattern . It was really taught by the people that invented this on Facebook . It divides the things by queries and mutations , and I 've tested heavily . What 's the challenge ? So the initial LLMs that we had access to , especially from OpenAI , I 'm giving it . And on the basis of this , I create like a subtree because this thing generates So there are two things reference here to types . There is vacations input and employee . This has not like further reference to other types . And then I come to employee here , and there are no further references . So I 've been implementing strategies for this . So one strategy kind of infers what do I need to use on the basis of the description . So let me show you , to Michal and Shonda , are very familiar . with these descriptions . and then identify or just use that strategy of the top K to know which ones should I include . Then I create this like sub tree that fits in most of the time in the GraphQL . Then I can use this . There is another strategy where I directly ask the LLM . So instead of using embeddings , I ask the LLM as if they were tools . That is the thing that is now like very popular . So I asked the LLM , this is the query I have . with their own descriptions . And then on the basis of this , I create again , these like sub tree of the GraphQL , and then I can obtain the query . with using the LLM in the case of , says me concretely , that it 's the use case that Adam wanted to test . This thing has so , the number of queries is so big , So let 's say , let 's say with GitHub . Let me see . So this is the query I 'm giving for the Rails organization , get the Rails repo on the last full request with the status open . This is the GraphQL that I 'm passing . The schema strategy , I 'm using embeddings . So I 'm just creating the embeddings and then getting the top K , rebuilding that tree so I can fit it to the LLM . Sorry . This is in an unstable state right now . Let me try to uncomment some things that I 'm thinking right now . Let me test another one , stars . Yeah , it 's better for me to use the LLM strategy here . So this usually can take a while . So there are even some cases where the GraphQL is so big that even after skimming it and just getting the parts , it 's too big . But with the Anthropic LLM , I can make it , idea is that you have a human query , then you have a description of the mutations and queries that you can take . But to be able to feed that to the LLM , you need a strategy to tell the LLM which parts it needs to use . how big it is , not even in the bigger ones , in the bigger Anthropic . So it 's 58,000 lines . And maybe make an average of two tokens per each . So that crosses even the 100K window of this LLM . So I just need to pick the entities that are relevant with whatever strategy . Right now there are two , like LLMs and embeddings . with whatever strategy . Right now there are two like LLMs and embeddings . and let me show it for you . Quick question . Do they all have like the really verbose comments there ? All the GraphQL queries ? Are they all , you know , do they have rich comments like that ? shrink that by eliminating those . Yeah . Right now that 's one of the requirements for the strategies . Because if you got rid of the comments , then the LLM would not maybe know as well . Yeah , as well . Yeah . because of the lower tokens , but then , you know , depending on whether the variable names are self-describing enough . Exactly , exactly . So I 've implemented some strategies . the tools that I have available . And then when I include the GraphQL , It 's all about like trying to save like characters always , not just for like cause reasons , But yeah , all of those combinations are available . and it might work if these variable names are self-descriptive . As you have seen , this one , it 's really without any comments , and it works pretty well . Let me show you how these things work . There is this Explorer from ... Let 's see . I asked this , get the ROS projects with most stars . so it 's , like , ordered . And then you 've got the stars and then you can . So that 's , let me try another one . Yeah , and maybe I could share a use case that what we were talking about , KTC , and maybe the others on the call have already seen it in the chat , but with that kind of US federal initiative says me the smart manufacturing Institute and then the think IQ platform they 're building . They 're really pushing tons of small medium sized manufacturers to leverage these open data standards to collect data for like incompatible appliances , like let 's say mixers on a manufacturing line from different manufacturers that do n't interoperate . let 's say mixers on a manufacturing line from different manufacturers that do n't interoperate . to do that with just their knowledge . then improving the GUI interface that they have , And I think where we can step in potentially what we 've been exploring is to go beyond the GUI interface where it 's like a lot of , they use GraphiQL actually , a lot of like pointing and clicking to select the specific appliances and data elements . How do we take that a step further and basically use language like JDC is describing here to say , Hey , I want to get a historian graph for all of the mixers that we had on the line for the last four Saturdays because you know , So that 's the idea to spit out a graph QL endpoint that would put that specific data for them , right ? That 's kind of the idea we 've been exploring at least . but by just describing . for a given instance after we 've specified time range . 1690 , max 10 samples within the start time , blah , blah , blah , end time . of more things , just the first , Yeah , I see that that 's an example . like English , right ? would be able to think about the information they need and have an awareness of that . And honestly , most engineers in manufacturing spaces are familiar with that type of notation , through this interface , then that 's incredibly robust . Exactly right . Yeah , because I 'm using Anthropic , That 's another story of like tweaking the prompt . then use the cheaper models that are faster . So right now it 's in a state that it 's like a Frankenstein , because I 'm using some parts from OpenAI and other from Anthropic . But right now it 's like the embeddings . It 's using like embedding from OpenAI and getting the tools that I need to use . And then when I get the GraphQL , I use it in Anthropic , Sesame 's GraphQL , it 's like , whoa . 15,000 , yeah . Yeah , 15,000 . Just let 's say like 30K , 30K tokens , making an average . So that goes into every prompt . It has to have all 30,000 tokens , so you 're left with 70,000 for our response , essentially . Or no , 70,000 for context , I guess . as context , that it 's the prompt plus all the data that I include , that it 's in context data , and that includes the GraphQL description . So that 's why I need to like to save as much as possible , trying to squeeze and getting just the parts that are relevant to the query . request . No , I 'm not . I 'm not . I 'm not like right now . I 'm not sampling that , but it 's less than that because the whole idea . I mean , once let me , let me explain you better . So the strategy that my point , but I think that the Miha and Sean , do you get the point ? Like it 's these things like reference other types , so you need to include them like all . Yeah , yeah , you do like an LLM guided tree shaking to minimize the input code . Yeah , yeah . And on the basis of this , I kind of like , how do you say , cut this huge tree of GraphQL . Like tree shaking , yeah . That 's basically . Yeah . To include just the things that I will know . And all the dependencies . Yeah , exactly . Yeah . Is it only the human language descriptions that I use for Anthropic . You must use the following criteria , blah blah , blah , context , date , time . Like these rules , the context , date , time , and that 's it . Yeah , but on the OpenAI side , when you generate the embeddings to find what you want to use from this . Let me show you . So I came up with this like a strategy . So there is this general thing , schema 'm passing , I return the whole schema . LLM strategy . So , it works like this . Get tool descriptions by operation . So , what it basically does , it gets the ... I mean , it 's easier to show it here . So , let 's say I get this , just this part that says code of conduct , And then I put two dots and say like this , look up the code of conduct by scheme . So I pass all of these in this format . You see here that key value . This is the descriptions of the tools . So it 's like , it 's the symbol name symbol name colon and then the comment . Yeah , yeah exactly . That 's the LLM strategy . So does it incorporate the comment on the type name as well ? Because it 's like the whole tree right or what ? Yeah and this list of tools separated by commas , answer the following question as best as you can , blah , blah , blah . And here you have the tool description . So that 's the format of code of conduct , comma . So that 's the LLM strategy . The other strategy is simpler . And it 's embedding strategy . So for the embedding strategy , I basically construct these documents that are the same thing , you see ? So for the LLM strategy , do you run the LLM once for every single field of every type in the source schema ? No , no , no , it 's not . I chunk this , like code of conduct to dot , look up the code of conduct by its key . Yeah , yeah . but I 'm not talking that case , but that 's not very hard to do . Yeah . and all the mutations and it still it works . It does n't work for Sesame . So that 's why I wrote embeddings . Because embeddings , you know , I just create embedding , Let 's say the tools are the queries and mutations shrink and tree , shrink and graph QL tree . and mutation descriptions . And then I create this document using the Java index capabilities . It 's just that , let 's say it will say like Enterprise and Lookup Enterprise in this . So you see here , for all in blah , blah , blah , get keys . And then I return the proper documents . So this is what it identifies the operations , order by a score , and then build the schema from operations . That 's what I call the thing . Once I know which queries or mutations I could be needing , this is the function works . But remarkably , it 's able to tackle these very huge schemas really well . You see ? You 've got it . JVC , what are your ? So two questions . One , I have n't seen if you put out a repo for this yet . I understand you 're refactoring . But if I want to run this on my own machine , are you going to be done refactoring soon ? Or what 's your thoughts on that ? open AI and for the GraphQL , So it 's here . What 's the other advantage of this ? awesome examples and maybe like two or three examples that like are totally out of scope and not feasible , and then take some time to demo that to them and maybe start the conversation us eager ? How could this make maybe some additional companies adopt this that are like , you know , they 're afraid of using a graph to a GUI to structure endpoints and then dump them into some sort of data explorer , right ? And then demonstrate the query , but then also maybe to be able to see the actual data being run itself . So if we put some sort of like a graphana type thing , whatever , on the third end there , I 'm wondering how much of this that , how elegant that could be really , right ? but at least maybe certain things it works with . Yeah , I 've tried with many of these queries , and give them extra details when those are missing , of all attributes . So query equipment , you see this one , equipment . My impression is that this kind of use case , that then they put into some like dashboard or anything . Because in the end , you will need , I think you will need some expertise because sometimes , unless you describe all the fields , it will miss some fields or unless you , let 's say , sometimes it just selects the first 10 . So unless you understand how to get rid of that . and specific interfaces for , again , key questions . Give me this particular data for these types of machines . Or give me a list of these machines . Or give me a list of these locations and all the machines , you know , and all the machines that are like the combination of all these queries . I think that that 's really how our customers are utilizing that to create these kind of custom reports . But like , what if that did n't have to happen ? And instead , you could have that natural language query that maybe works for like the simpler or majority of requests . And then you maybe it bypasses , I guess for instance , this one . A Grafana visualization of that , right ? but for any reason uncontrollable , it just got the first 10 . That 's another thing , in the GraphQL , but that 's another story . So there might be some inconsistency . Cause I just downloaded these from someplace here . Like , yeah . And in that case , we would need some sort of like a post-processor for these very specific errors , right ? To basically resolve them . Yeah . That 's ... I kind of see like more potential on some other use cases like general interface for general command line interface . There are some efforts on it . So that 's also worth mentioning maybe to the guys here . So these people from Stanford tried to make basically this kind of the same thing . So , scaling tools . So , these tool patterns , that is , you have some query and then you have some tools available to solve it , but you always have the that is some YAMA , and fine-tuned it on the instructions . That is some YAMA , and fine-tune it on the instructions . This is using tools such as Hugging Face Models and things like that . But it 's way more complex , in my opinion , I think , because they tried to format everything as function calls . And I think this thing has seen more ... rather than SQL or some function code . You know , there is this comas and things . GraphQL , it 's kind of simpler . You just know the fields . You might miss some fields and still the thing goes on . So it 's kind of in between in the spectrum of this contract . And on the other end , you have like things like REST , but in the , sorry , in the other end , you have just JSON , you have like REST and GraphQL . But there are many efforts doing this . And you know , right now also OpenAI has included natively a functionality to call , to do this kind of thing . I think behind the scenes , they are doing the same . So it does n't , one can just use the same thing and it will take advantage of the training that they put already . But underneath , it 's doing a very similar thing , I guess . It 's called OpenAI functions . Yeah , OK . For the graphic , sorry . Sorry , go ahead . them and get their perspective . And then , you know , I can summarize those learnings for us to think There is some ... It says that it has an error , but it 's not erroneous . That 's something I do n't understand sometimes with GraphQL . I instructed for the Rails organization , get the repo Rails and the last 10 pull request titles with open status . Let me show you . Sorry , Sharon , let me cut you off . I just want to close out that item . Yeah . So you can see here . Also , response request not issues . So , qualify association . It 's here , it 's in there . Get rid of unnecessary gem . You see it 's , and it 's kind of a complex query . I just said like for the Rails organization , get the repo Rails and the last 10 pull requests with titles with open status . And it has enums and things like that that are not trivial . This is an enum . This is this kind of nesting pattern that it needs to use . So I feel very confident with the thing . And it also did some good work with Sesme . One idea is that this can form the basis of some assistant , local assistant , so you could thing that I 've seen that people did with this Gorilla . So if you ... This is the ... That 's related with the other thing URLs , internal URLs ? These people are moving in that direction . Yeah , okay , yeah . like this text interface for many things . This is the one I was referencing , the AIP thing . Let 's say it receives an alert , and then it says , show me more details . You can just stuff the prompt , show me more details , but they are referencing these entities . So you know , immediately what 's the query that it 's involved there and even the IDs that you can like stuff into the prompt . So this is the one dimension that was the motivation to start with this . And it 's remarkable that these guys , there is some place where it 's shown that they are using open source model here . You see , they disclose this . So they 're using Flan , GPT-NEWX . Thank you , God . I got all of these screenshotted . You can go to AIP , or maybe at the start of ontology prompt . And I was analyzing all of these screens that they disclose . Yeah . Remember , they also disclose some very interesting thing here of how they work . So they just use the LLM as some other user . They do n't have this problem of what it can access or not . It 's just like another user . So whatever that user has access to , the LLM has access to . And this is the actions that it can take . They include one thing called suggestions . Yeah , that 's a main thing that they advertise , just like , figure out LLM security . Look , this other thing , this other thing has also a bunch of clues of how they , so instead of getting this PII problem embedded into the model , they just put an input filter to whatever PII is involved . They just cut it , then it 's the model , and then there is the validation . Very cool , yeah . Sorry , Tom , you were about to ask a question earlier . Yeah , so for the output of the GraphQL , are you using the constraint generation or whatever ? Or is it just opening the syntactically correct GraphQL on its own ? it 's open and it 's working well . I 'm not like constraining it to some like concrete schema . with knowledge of the schema . Yeah , definitely . But right now , it 's not constrained at all . Yeah , the only protection that I have right now for this . You validate afterwards , right ? Oh , I do two things . Like , let do two things . Let me show you . I think here it 's in main . Oh , okay . because there could be a bunch of errors . GraphQL at all , but I 've never encountered that . but the prompts that I 'm using are already like covering for that . like , hey , take into account that this data , it 's in this format , something like that . for GraphQL queries or mutations . Oh , like to extract the part of the result . Yeah , and then I do the validation . But I 'm really not very concerned . I think right now this is not a problem . I mean , it behaves pretty well . Okay , in that in that front . But yeah , you could like constrain I think there are some efforts and I there I read a debate of what was I read a debate of what was OpenAI really doing , because you could do two things . One , it 's this open-ended thing , and then constrain it with regex . And in the case that it misses , you can feed it back and tell it , hey , this is bad . the valid ones . That 's another solution that I 've seen . And finally , it might be the one that you have in mind that it 's like constrained , that you have to hack into the LLM latest layer , and then you can squash the probability because in that layer , you will have one output per token , so there will be some invalid tokens . There 's some guy that did that . Yeah . That 's kind of the approach that Gorilla ... They do n't need this . They are able to chunk thousands of tools without having to select the tool . It 's just the training that speeds that . Yeah , they did say . But it has some small errors . I think I prefer to have a way more powerful LLM rather than have that ... From what I 've seen , it 's very easy just to use the regex and then validate . Yeah , fair . Especially since so much of this is plain language already . The way the function calls are , they 're kind of intuitive when you read them in a way , right ? Yeah . Yeah , I 've seen that this model , because it 's this fine-tuning , foundational model really helps in that situation . from English to Chinese if you come here . And it selected the French model . So there should be , I do n't know why they include this example in their showcase , but they are being honest with that . So it 's like , how do you call that ? It 's like overfitting because you 're not even able to generalize these codes . You just use the model . completely biased , it 's like overfitted . So I kind of prefer the more general model than Google did this but for SQL . And if you read the paper like very , with a lot of attention , they did n't gain much by fine tuning . You are comparing it with others . Look at the figures . The difference between fine-tune and the other one was just like 1 % . Put the analysis here . Yeah . 77.3 to ... Look3 . 77.3 to 78.3 . Look , so the only difference ... Okay , this is the whole dataset . Sorry . So , the difference between a few-shot stuff model to a fine-tuned model , it was just 1 % . So , I really prefer to have the few shots . That 's something that is also emerging . samples to stuff in . And that might work better than just fine-tuning and that 's like costly . They changed their docs , but let me search for samples . Wait . Or read Or retreaters . Well , they have this concept , you know , that on the basis of the prompt , they fetch the most relevant view shot samples to stuff in . And according to what I 've seen , it might work better than just like fine-tuning . Yeah , but at some point it might make sense to fine-tune . Yeah , this is very exciting . I 'm looking forward to running it on my own machine and kind of understanding a little bit deeper . And yeah , exploring more use cases , that sounds really exciting as well . Yeah , so I play with ... Let me ... Can be stuffy . But it did work also for these huge GraphQLs . I 'm not using toy things . GitHub . Sorry ? Yeah . Well , at this point , just to comply with monadicals thing , sending the . Yeah , and that 's where Sean 's ideas about how to overcome the context window size and local processing would maybe help . If it was feasible . Not necessary . No , it 's just using a privately hosted LLMs . I 'm using Anthropix and OpenAI . It 's crazy . But definitely with the local models , we have n't found a way to work with that . Plus , you know , if some of them , it 's like , We actually have a preprocessor to resolve what we 're seeing on the screen right now . But yeah , there 's still some struggles on the local model that we have to figure out and get creative with . Okay , I 'm going to stop the recording unless anybody else has any last questions model could be useful for the token . Contact size problem as well . Like if something that could be applied to the scheme . Get rid of this . Anyway , that 's all I just wanted to mention . Yeah , yeah . Awesome . Hey , thanks , everyone . \"" ] }, - "execution_count": 39, + "execution_count": 32, "metadata": {}, "output_type": "execute_result" } diff --git a/setup_dependencies.sh b/setup_dependencies.sh index fd7d9e32..951dcb38 100755 --- a/setup_dependencies.sh +++ b/setup_dependencies.sh @@ -1,4 +1,4 @@ -# Upgrade pip + Upgrade pip pip install --upgrade pip # Default to CPU Installation of JAX @@ -24,3 +24,10 @@ pip install git+https://github.com/sanchit-gandhi/whisper-jax.git # Update to latest version pip install --upgrade --no-deps --force-reinstall git+https://github.com/sanchit-gandhi/whisper-jax.git +pip install -r requirements.txt + +# download spacy models +export KMP_DUPLICATE_LIB_OK=True +python -m spacy download en_core_web_sm +python -m spacy download en_core_web_md + diff --git a/viz_utilities.py b/viz_utilities.py index 1606720a..7cd41d66 100644 --- a/viz_utilities.py +++ b/viz_utilities.py @@ -1,6 +1,6 @@ import matplotlib.pyplot as plt from wordcloud import WordCloud, STOPWORDS -from nltk.corpus import stopwords as nltk_stopwords +from nltk.corpus import stopwords import collections import spacy import pickle @@ -15,7 +15,7 @@ config.read('config.ini') en = spacy.load('en_core_web_md') spacy_stopwords = en.Defaults.stop_words -STOPWORDS = set(STOPWORDS).union(set(nltk_stopwords)).union(set(spacy_stopwords)) +STOPWORDS = set(STOPWORDS).union(set(stopwords.words("english"))).union(set(spacy_stopwords)) def create_wordcloud(timestamp, real_time=False): """ @@ -195,4 +195,7 @@ def create_talk_diff_scatter_viz(timestamp, real_time=False): width_in_pixels=1000, transform=st.Scalers.dense_rank ) - open('./scatter_' + timestamp.strftime("%m-%d-%Y_%H:%M:%S") + '.html', 'w').write(html) \ No newline at end of file + if real_time: + open('./real_time_scatter_' + timestamp.strftime("%m-%d-%Y_%H:%M:%S") + '.html', 'w').write(html) + else: + open('./scatter_' + timestamp.strftime("%m-%d-%Y_%H:%M:%S") + '.html', 'w').write(html) \ No newline at end of file diff --git a/whisjax.py b/whisjax.py index 4264ffce..e0cce47f 100644 --- a/whisjax.py +++ b/whisjax.py @@ -26,8 +26,8 @@ from file_utilities import upload_files, download_files from viz_utilities import create_wordcloud, create_talk_diff_scatter_viz from text_utilities import summarize, post_process_transcription -nltk.download('punkt') -nltk.download('stopwords') +nltk.download('punkt', quiet=True) +nltk.download('stopwords', quiet=True) # Configurations can be found in config.ini. Set them properly before executing config = configparser.ConfigParser() @@ -141,7 +141,8 @@ def main(): "transcript_with_timestamp_" + suffix + ".txt", "df_" + suffix + ".pkl", "wordcloud_" + suffix + ".png", - "mappings_" + suffix + ".pkl"] + "mappings_" + suffix + ".pkl", + "scatter_" + suffix + ".html"] upload_files(files_to_upload) summarize(transcript_text, NOW, False, False) diff --git a/whisjax_realtime.py b/whisjax_realtime.py index 9144f173..b0503b17 100644 --- a/whisjax_realtime.py +++ b/whisjax_realtime.py @@ -12,7 +12,7 @@ from viz_utilities import create_wordcloud, create_talk_diff_scatter_viz from text_utilities import summarize, post_process_transcription from loguru import logger import nltk -nltk.download('stopwords') +nltk.download('stopwords', quiet=True) config = configparser.ConfigParser() config.read('config.ini') @@ -118,7 +118,8 @@ def main(): "real_time_transcript_with_timestamp" + suffix + ".txt", "real_time_df_" + suffix + ".pkl", "real_time_wordcloud_" + suffix + ".png", - "real_time_mappings_" + suffix + ".pkl"] + "real_time_mappings_" + suffix + ".pkl", + "real_time_scatter_" + suffix + ".html"] upload_files(files_to_upload) summarize(transcript_with_timestamp["text"], NOW, True, True)