Kaushik Govindharajan

India is not just catching up in the AI race; we're innovating and leading in ways that are uniquely ours. The Economic Times recently highlighted how our approach to Generative AI goes beyond just Large Language Models (LLMs), addressing the specific challenges and opportunities within our diverse market. Rahul Agarwalla, Managing Partner at SenseAI Ventures, shared his invaluable insights into this AI revolution. His leadership and vision are truly driving innovation in the field, and it's an honour to be part of this journey with him. For anyone interested in the developments in AI and how India is making its mark on the global stage, this is a must-read.

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Welcome Prof. Biplav Srivastava to IIT Kharagpur AI4ICPS I Hub Foundation ! We are keen to learn more about Trusted AI and how it can be applied for the betterment of society in a sustainable way.

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Fantastic panel on GTM for Enterprise AI. Thanks to fellow panelists for a sharp discussion and to Emergent Ventures for hosting. Anupam Rastogi Ankur Jain Preethy Padmanabhan Chandini M Ammineni Jason Griggs Deb Bardhan #GTM #EnterpriseAI

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Our recent hiring post brought in over 500 applications, including a fantastic response from IIT candidates and other top talent across the country. We’re thrilled by the interest in joining our mission to shape the future of robotics and AI! But here’s what we’re really looking for: beyond resumes, we want to see portfolios that showcase your passion and hands-on experience. Whether you’ve developed robots, crafted AI models, or led impactful projects, a portfolio is the best way for us to understand your skills, creativity, and problem-solving approach. Why does a portfolio matter? • It shows us how you translate ideas into reality. • It highlights your technical abilities and real-world experience. • It’s a chance to make your application stand out with tangible proof of your work. If you have a portfolio website, even better! It gives you an edge by providing us with a detailed view of your contributions and projects. To everyone who has applied or plans to – thank you! We’re excited to learn more about your work and how you can contribute to our journey of innovation at I HUB ROBOTICS 🇮🇳🦾 #Hiring #RoboticsCareers #AIInnovation #PortfolioMatters #FutureOfTech #IHUBRobotics #HiringNow #NowHiring #TechJobs #AIJobs #RoboticsCareers #JoinOurTeam #ApplyNow #IHUBRobotics #FutureOfTech

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Here’s the #1 mistake EB-1A aspirants in tech make. ⚠️ They go outside-in versus inside-out. What does that even mean? It means they look externally for how other people built EB-1A profiles as a guide to how they should build their profile. I get it - if you don’t know where to start, makes sense to do what other successful applicants do, right? Wrong. This approach is breeding a generation of EB-1A’s that all look the same. 🐑 The whole point of the EB-1A process is to show why YOU are UNIQUELY recognized as among the best in your field. 💯 So how does it help to get all the same judging, awards, and media that everyone else is getting? ✅ You are supposed to stand out from the crowd, and show the impact of the work YOU are doing within the EB-1A framework. Plus, in tech, everyone has a different story to tell. How does it help to use someone else’s approach to tell your story? These EB-1A’s come across as fake - and you know who hates fakers more than anyone else? 👮‍♂️ USCIS. And when they see these applications they will profile you as a faker and completely disregard the parts that are deserving. We know because we (and many of our lawyer colleagues) are now being asked to help scores of tech workers who got their EB-1A’s denied after filling up their profiles with unimpressive awards and marketing exposes masquerading as media articles in 3rd rate publications. Question: since when do awesome tech employees ever get recognition of their expertise in the press? They don’t. Their employers do. So it looks weird that a generation of employees are now suddenly getting press coverage. ✅ Instead of an outside-in approach, go inside-out. First identify your unique impact proposition. What is your narrative? How are you uniquely amazing? Because if you are a senior employee at an innovative company, chances are you doing some incredible, impactful EB-1A-worthy work! Then, build your case from there in a way that honors that narrative. This is the formula we use in our course, and then in our law firm, that leads to a ~99% approval rate. Don’t be tempted to fake it! #immigration #eb1a #globalmobility -------- Do you work in high-tech, are stuck in long green card backlogs, and are looking to level up to an EB-1A? Our next attorney-led live EB-1A profile-building cohort begins on June 8. Apply now to secure your spot! The link is in the comments below.

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AI in Local Government: City of Boston's Interim Guidelines for Using Generative AI (Part 2 of Series) Overview: The City of Boston has taken a proactive step in addressing the use of AI in local government by releasing interim guidelines for using generative AI. These guidelines aim to encourage responsible experimentation while managing potential risks. Target Audience: All City of Boston employees and agencies (except Boston Public Schools) Key Features of the Guidelines: • Principles for AI use (e.g., Empowerment, Inclusion, Transparency) • Specific guidelines for content generation and review • Sample use cases and examples using ChatGPT and Google's Bard • Do's and Don'ts for various AI applications • Resources for further learning Standout Elements: • Encourages responsible experimentation • Addresses privacy and security concerns • Provides actionable examples for common municipal tasks • Emphasizes transparency and accountability in AI use Key contacts: • Santiago G., Chief Information Officer, City of Boston • Department of Innovation and Technology: [email protected] Personal comment: Boston's AI guidelines are one of the first publicly released by a U.S. city. What impresses me is the balance between innovation and responsibility. It's not just policy; it's a practical toolkit with real-world examples using ChatGPT and Bard. For cities wanting to experiment with generative AI but needing guardrails while developing comprehensive policies, this is an invaluable resource. It's refreshing to see a city embrace new tech thoughtfully, with an eye on inclusivity and transparency. Boston's approach offers a solid starting point for any municipality navigating the AI landscape. Link to Boston's AI Guidance: https://lnkd.in/gTDhCh8w #AIinGovernment #SmartCities #ResponsibleAI #BostonInnovation #AIPolicy

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Here's why prompt engineering is one of today's most valuable skills. VentureBeat recently published an article by Deven Panchal of AT&T Labs. I applaud Deven for his vision. He says, "A well-crafted prompt can significantly impact the quality and relevance of the output of LLMs." So many are refusing to accept this. Mainly because prompting uses natural language. They are misguided, assuming AI can expertly prompt for them. Even if it can someday (which I doubt), it can’t today. The closest thing is SmartGPT 2.0, which still can’t compete with an expert prompt engineer. I recommend learning and practicing prompt engineering. 🟢 If you don't know where to learn, comment "START" and I'll point you in the right direction. --------------------------------------------- See comments for a link to the full article. 🔗 Follow 🔔Mark Fulton for more on #AI #Prompts #AIAgents

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I'm so excited about the problems "traditional" software companies are tackling right now. LLMs let software teams move faster, make sense of larger domains, and built much more complex tech than we were able to even five years ago. I believe the impacts in healthtech, govtech, and fintech will be large. Simultaneously, I'm amazed at all the ways one can lose money investing in AI companies - especially the foundational models. There's no part of this market that isn't trending toward commoditization. This has been true for a while but the release of llama3.1 makes it especially clear: Most workflows can retrain on this open-weight 405B model with no change to their budgets (AWS Bedrock charges *at max* the same as OpenAI) and then find ways to negotiate/optimize that cost way down while not sending their data away to a 3rd party. Even the B2C story is commoditized — what AI wrappers have believable ROI if I can run this one-liner and the hard part is accomplished for a fraction of a cent?: aws bedrock-runtime converse --model-id meta.llama3-1-405b-instruct-v1:0 --messages '[{"role":"user","content":[{"text":"Write me a post enumerating how investments in LLMs may yield no competitive advantage."}]}]' As I look past the flashy parts of AI I see: * Building one-off tools against novel APIs is now (and forever) instant * Analyzing requirements for most tasks and understanding new domains is an order of magnitude faster * GitHub Copilot yearns to write React for us * LLMs give the same boost as pair programming at zero cost I haven't been this excited to build complex products in a long time.

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Had a great conversation with Jabari Young from Forbes about the $13.8 million AI Squared just raised in Series A funding, led by Ansa Capital and New Enterprise Associates (NEA). It’s exciting to watch AI Squared grow, because helping organizations deploy and streamline their use of AI is something I’ve been working on for a long time. During my time at the National Security Agency, I started thinking on how to accelerate and streamline the way organizations adopt AI. Leading their data science team, I saw first hand that many of the AI/ML solutions developed were never actually able to keep people safer - and that mattered to me, because I had two brothers deployed overseas. I knew then I wanted to fix this problem. I went to Databricks to better understand how to incubate a technology and bring it to market - and worked with Matei Zaharia, Ali Ghodsi, Ion Stoica, Pete Sonsini, Greg Papadopoulos, Luke Cooper and so many others who helped me understand what it is to build a great business. I work now with talented people who bring experience from the data science and technical teams of Microsoft, JPMorgan Chase & Co. Chase and the United States Department of Defense, and I am grateful for the growing number of people invested in AI Squared’s success. As part of today’s investment, Roger W. Ferguson, Jr., former Vice Chairman of the Federal Reserve and board member of Alphabet Inc., has also invested and will join the company’s Board of Directors. Ansa Capital co-founder and General Partner Allan Jean-Baptiste will also join AI Squared's board. I’d like to thank Ansa Capital for leading this funding round and existing investors New Enterprise Associates (NEA), Latimer Ventures and Ridgeline. We’re excited to use this funding to expand our team and mature our platform - because we’re invested in helping businesses truly maximize the value of AI. Read more about the funding round and AI Squared of Forbes here: https://lnkd.in/edTdauaZ

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Exclusive: Health-care AI startup Suki on Wednesday announced it's building patient summary and Q&A features with Google Cloud as it looks to push beyond clinical documentation. Suki’s flagship product, called Suki Assistant, allows doctors to record their visits with patients and automatically turn them into clinical notes, helping physicians avoid the headache of manually writing out all of that information. The new features with Google Cloud will allow Suki to provide clinicians with more assistive tech as they care for patients, the startup said. It is the next frontier for the seven-year-old company. “We were never really building a clinical documentation tool only, it was supposed to be an assistant,” Punit Singh Soni, the founder and CEO of Suki, told CNBC. “An assistant can help you with documentation, but it can also start doing other things.” More details here!

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Very interesting to see the effect that the relicensing of Redis had on the development community. "Redis [...] shows a substantial difference in organizational dynamics, which is not unexpected given that there were employees from 12 other companies contributing to Redis who were disenfranchised by the licensing change. The employees from those 12 companies stopped contributing after the relicensing event, and most of them began contributing to the fork, instead, which brought the number of outside contributors with 5 or more commits in Redis to zero in the 6 months after the relicense."

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Easy way to understand the DOs and DON’Ts for LLMs today: 𝐃𝐎𝐬: 🔵 Do choose the right LLM for your use case. Also, righ model type and size 🔵 Use LLMs for tasks like research, writing assistance, summarization, ideation, get suggestions, understanding, learning, generating text, and coding support 🔵 Prompt the LLM carefully and validate its outputs. Prompting is your best friend. Fine-tuning prompts based on initial outcomes 🔵 Recognize the importance of data governance 🔵 See how to orchestrate AI agents 🔵 LLMs are evolves. Keep that in mind, and monitor their results. 🔵 Just play/try them. Ajust temperature, Top K, and Top P and try it again. 🔵 Use guardails 🔵 Good data create good results 🔵 Understand the model's training data, and limitations (this is key). 🔵 Choose the optimal infrastructure 𝐃𝐎𝐍'𝐓𝐬: ⚫ Don't assume the LLM's outputs are 100% accurate or factual, or is your final step. Not at all. Fine tunning! ⚫ Don't share personal information or sensitive data with the LLM. Review the platform and LLM that you are using. Security is crucial, you can see here how to have the full control over the data you use to customize the foundation models for your Gen AI apps. https://lnkd.in/dx5U4zmP ⚫ Don't start from scratch ⚫ Don’t let LLM costs grow out of control 𝐊𝐞𝐲 𝐓𝐚𝐤𝐞𝐚𝐰𝐚𝐲: LLMs can be powerful tools, but require careful and responsible use to mitigate risks. Understand their capabilities and limitations to use them effectively and safely. Check this 𝐢𝐧𝐟𝐨𝐠𝐫𝐚𝐩𝐡𝐢𝐜 (simple to undertand): https://lnkd.in/dFtJSJHf #AWS #GenAI #LLM Tasks and models (of course there are more and betters for particular use cases/tasks, however this is a suggestion):

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It blows my mind to see how much time and $$$ enterprise AI leaders are spending on human evaluation of LLM responses — AI development cost/time sink has shifted from human labeling to human evaluation. Few thoughts on the critical state of AI evaluations today: 1. **There is an over reliance on human evaluations** — human in the loop is important, but it being the sole evaluation mechanism leads to ‘vibe checks’ and biased responses. ‘Red teams’ in enterprises as the first line of defense are a huge time and cost sink. 2. **Using ‘GPT as the judge’** seems to be the popular mechanism to introduce ‘auto-evaluations’. This is concerning on 2 counts: a. Using an LLM to judge another LLM can lead to recursive failures b. The super high cost of GPT evals along with increased latency makes this a non starter for evaluating production applications A bunch of enterprises are now spending more on evaluation than on LLM inference! What we need in the AI community: — More R&D spend on evaluation mechanisms that are cheap, low latency and don’t rely on GPT. — Systems that bring together these evaluation mechanisms along with humans in the loop to evaluate AI systems faster, better and cheaper. Those that have kept a close eye on us know that this line of R&D has always been a big focus for the research team at 🔭 Galileo — big announcement coming soon here!!

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In the evolving landscape of Vertical AI startups, identifying effective entry strategies is crucial. Tanay Jaipuria's recent analysis highlights four prominent "AI wedges" that startups are leveraging to penetrate specific industries: Voice Automation: Implementing AI-driven voice agents to handle customer interactions, enhancing efficiency in sectors like retail and healthcare. Unstructured Data Parsing: Utilizing AI to convert unstructured data into actionable insights, streamlining processes in finance and logistics. Verticalized Search: Developing specialized search tools tailored to industry-specific needs, improving information retrieval in fields such as legal and biomedical research. Content Generation: Employing AI for industry-specific content creation, aiding marketing and customer engagement strategies. These strategies enable startups to address unmet needs within industries, facilitating rapid adoption and growth. As AI continues to advance, how do you foresee these wedges evolving, and what new opportunities might emerge for startups in specialized sectors? Share your thoughts in the comments below.

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A headline from Matthew Tower's excellent ETCH Weekend Read newsletter and Substack (https://www.etch.club/) about all things #edtech states : "Further proof that no one knows anything about AI and we’re just making up the rules as we go: 2 Emory students win $10K cash prize *from Emory* for creating AI homework help tool. Emory then suspends students because tool “could be used for cheating.” / via Wall Street Journal." Here's the Wall Street Journal's LinkedIn post on the article: https://lnkd.in/dnFGfqjB Here's a link to the tool itself: https://www.eightball.ai/ Technology, education, and policy fronts are all moving or being moved to embrace, harness, grapple with, and/or regulate what is undeniably a cultural and generational-changing tool. Thoughts?

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THE DYSTOPIANS The Tech Baron Seeking to “Ethnically Cleanse” San Francisco If Balaji Srinivasan is any guide, then the Silicon Valley plutocrats are definitely not okay. Balaji Srinivasan speaks during the Singapore Fintech Festival in 2022. BRYAN VAN DER BEEK/GETTY IMAGES Balaji Srinivasan speaks during the Singapore Fintech Festival in 2022. To fully grasp the current situation in San Francisco, where venture capitalists are trying to take control of City Hall, you must listen to Balaji Srinivasan. Before you do, steel yourself for what’s to come: A normal person could easily mistake his rambling train wrecks of thought for a crackpot’s ravings, but influential Silicon Valley billionaires regard him as a genius. “Balaji has the highest rate of output per minute of good new ideas of anybody I’ve ever met,” wrote Marc Andreessen, co-founder of the V.C. firm Andreessen Horowitz, in a blurb for Balaji’s 2022 book, The Network State: How to Start a New Country. The book outlines a plan for tech plutocrats to exit democracy and establish new sovereign territories. I mentioned Balaji’s ideas in two previous stories about Network State–related efforts in California—a proposed tech colony called California Forever and the tech-funded campaign to capture San Francisco’s government. Balaji, a 43-year-old Long Island native who goes by his first name, has a solid Valley pedigree: He earned multiple degrees from Stanford University, founded multiple startups, became a partner at Andreessen-Horowitz and then served as chief technology officer at Coinbase. He is also the leader of a cultish and increasingly strident neo-reactionary tech political movement that sees American democracy as an enemy. In 2013, a The New York Times story headlined “Silicon Valley Roused by Secession Call” described a speech in which he “told a group of young entrepreneurs that the United States had become ‘the Microsoft of nations’: outdated and obsolescent.” “The speech won roars from the audience at Y Combinator, a leading start-up incubator,” reported the Times. Balaji paints a bleak picture of a dystopian future in a U.S. in chaos and decline, but his prophecies sometimes fall short. Last year, he lost $1 million in a public bet after wrongly predicting a massive surge in the price of Bitcoin. Still, his appetite for autocracy is bottomless. Last October, Balaji hosted the first-ever Network State Conference. Garry Tan—the current Y Combinator CEO who’s attempting to spearhead a political takeover of San Francisco—participated in an interview with Balaji and cast the effort as part of the Network State movement. Tan, who made headlines in January after tweeting “die slow motherfuckers” at local progressive politicians, frames his campaign as an experiment in “moderate” politics. But in a podcast interview one month before the conference, Balaji laid out a more disturbing and extreme vision. https://lnkd.in/d-5byJhp

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