PSankalp Patro

This is f*cking hilarious: TuSimple's pivot from self-driving trucks to AI animation and gaming! 🤖🎮 Right now, everyone’s betting on humanoid and general-purpose robotics startups. But after 5 years in self-driving tech and building Kopernikus Auto, here’s the reality: most humanoid robotics companies will be dead. In the self-driving world, we’ve only seen a few real winners: Tesla, Waymo, and Comma.ai. Why?  - Humanoid robotics isn’t a hardware problem; it’s a software problem. - You either have infinite data, cash, talent, or a clear use case—or you won’t make it, no matter how much you raise. From over 100 companies, almost all in self-driving tech are dead or miles away from profitability. ✨ Don’t get distracted by the appeal of humanoids. Focus on real problems you can actually solve. What are you focusing on? 👇

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ANOTHER AI TABU BROKEN> #AI can #CONTROL #COMPUTER directly If anybody doubted then today's ANTHROPIC release just confirms that ... ... 1] AI is strongly walking (not even crawling, yes, already walking) to situation that it can #autonomously #act on the prompt provided. ... 2} #Anthropic is slowly taking over OpenAI and becoming leader not only in the quality of the models (Claude vs GPT), but also what it can do with those models. Comparing the "agents" release by OpenAI and Anthropic, OpenAI is far from having the upper hand. ... 3] Last call to think about what we set as acceptable and what not so in tasks handed over to AI. We are few quarters away from AI would be capable of doing whatever we allow it to do.

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After being encouraged by multiple friends to apply to YC with our new AI Career Agent (shout out / thanks Omri Mor, Saroop, Alan, Roham + others!), Beier Cai and I put together an application last week. YC is obviously an amazing place to grow a new product category like AI Career Asssistants, but what I was NOT expecting was the application video driving so much interest. After seeing a spike in waitlist applications, citing “YouTube” as a source, I checked out the video and saw it had already generated >1k of views! If you’re curious, here is a link to the vid. Let me know your thoughts! We are passionate about building Commit: AI Career Agents for Developers into something that ALL tech workers can use to increase their growth and impact!

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Last night I had the fortune of representing LaunchDarkly at Sourcegraph's CodeAI Summit NYC. An important theme I took from last night's event? Context. Models like specifics. Computers can't read our brains or know what we want to achieve. Technology is kinda useless without the right context. As we move forward in this increasingly AI-generated world (for better and for worse) let us not forget the importance of adding context to the equation. Whether that's providing context to a dataset through how it was collected, sharing context of your repo to better aid a code assist tool, or simply providing context behind the why of our decisions. It's an interesting (and important) place to keep in our minds. #AI #MachineLearning #DeveloperAdvocacy #DeveloperEvents

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Went overboard building agents at the AGI-House hackathon this weekend in SF. The idea was to build a personal AI agent which acts as your executive assistant, has access to your calendar, can chat with your contacts on Telegram & Slack, and can book an Uber pickup for you. Didn't they say, "the next big thing will start out looking like a toy"? Hacked away a crewAI + Open Interpreter demo in a few hours with Rahul Chhabra, re-realized how broken the agent build/flow engineering toolkit is. Still! Played around with OpenInterpreter 01 and experimented with a lot of verbal prompting to build/train new skillsets. Built out a tool for the agent where natural language instructions to OpenInterpreter were fed, and those got converted to AppleScript commands on the fly. Cherry on top, bagged a podium finish at the hackathon! 🥉 Agents are the future. 🚀 Github in comments.

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Over the years I’ve seen a lot of things in Silicon Valley. One thing that hasn’t changed much? People making the same mistakes about equity compensation, taxes, and risk. That’s probably because the Bay Area has so many talented software engineers, who tend to have a “do-it-yourself” mentality. However, when dealing with complex matters where human behavior and specialized knowledge play crucial roles, a collaborative 'buddy system' almost always leads to better outcomes. 👥 If you'd like to work on any of the 5 items below and want to try out the 'buddy system', send me a DM. 🤝 #rsus #taxes #microsoft #meta #apple #google #Nvidia #amazon #tesla #magnificent7 

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Day 3/3 GenAI Summit San Francisco Causal AI, causal grounded RAG - cRAG, scaling from POC to production in AWS, a deep dive into the evolution of Llama models and what's coming next, synthetic data in the age of genAI, PII, and domain randomization. I can't count how many times I've heard the words AI, genAI, data, cloud, RAG, LLM, and multimodal in the last 3 intense days. And when I finally went to have lunch at a restaurant, at the adjacent table, a fintech AI startup founder was pitching to a VC, while the people at the table behind me were talking about data engineering. It feels so good to be in SF, where at the airport’s security check-in a big Anthropic advertisement greets you! 😊 The last 3 days were amazing, filled with inspiration and thought-provoking new tech. I can't wait to get back to building DiffuseDrive and working with our customers!

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Replacing an expensive generalist LLM like GPT-4 with a cheaper more specialized model like a fine-tuned Mistral 7B is a tried and true approach to really drive your GenAI expenses down. We've got a handy guide on how to start your fine LLM cost optimization journey with OpenPipe for fine tuning and OctoAI for model serving https://lnkd.in/e8udh8de

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Carta's data is ....off? Coastal Recruiting communicates with hundreds of engineers weekly, primarily in New York and San Francisco. We consistently encounter software engineers with 2-6 years of experience requesting base salaries between $180,000 and $250,000, plus equity. Perhaps "misleading" is a better term, as I frequently hear founders saying, "But Carta indicates we can hire this engineer for $140,000 to $160,000." We then observe Seed/Series A companies paying $200,000 to $300,000 for top talent. The disconnect may stem from the fact that companies raising funds from Sequoia, Khosla, Founders Fund, Lightspeed, a16z, KP, Greylock, Index, NEA, Lux, and others are not seeking what 95% of the companies providing data to Carta are seeking. These companies are looking for the top 0.01% of engineers. I say all this while also acknowledging my appreciation for Carta. I value the data and charts it provides, but it's important to remember: "There are three kinds of lies: lies, damned lies, and statistics."

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There was a time when people paid $200-$300 for a single prompt. Now, LLMs themselves are better prompt engineers than humans. It’s interesting how quickly things change in less than a year. LLMs went from small 7-50B parameter models, all the way up to +1T parameters (parameters determine how “smart” the LLM is). With it, the bar for writing good prompts has dropped to nothing… P.S. For those shaking their heads, yes, LLMs in production still require significant work. Open-Source LLM prompting remains tough and requires thorough testing.

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Everyone's talking about “founder mode,” but as it gains traction, founders will start using it as an excuse for poor management. Founder mode isn’t a license to run a company at 5,000 the same way you ran it at 5. Jensen Huang, CEO of NVIDIA, exemplifies what I like to call “scaled founder mode”. Scaled founder mode is being highly involved in the most important things, that only you can do to drive the company forward. Nvidia is one of the most successful tech companies in the world, with a $3 trillion market cap. And Huang, with a 31+ year tenure, is the longest-serving CEO in the industry. He’s a highly effective manager. And he’s still very much in founder mode. When interviewed by Stripe's Patrick Collison, Huang said “CEOs are pinch hitters. We should be working on the things that nobody else can or nobody else is.” Nvidia’s leadership team of 60 reports directly to Huang. But he doesn’t do 1:1s. This way, the team of 60 is relatively flat, with no silos and no privileged access to information. Not saying that killing 1:1s is the answer to speedy execution. But Nvidia found that this way, everyone contributes to solving problems with equal access to important info. And because Huang sees his primary role as being a custodian of the culture, he eats in the cafeteria with employees every single day. At almost 30k employees, you can’t get much more “in the details” than that.

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Keep Learning New Things... Indeed, the path to efficiency requires discipline, consistency, and sacrifice. I can't believe that it is already the 3rd week of the Headstarter Fellowship! To be honest, I felt quite lazy throughout this week, with low dopamine levels. However, I'm getting back on track and am ready for the next week of the fellowship. During the previous week, I had the opportunity to work on some exciting projects: - The Pantry App Project: I focused on the Firebase backend, learning how to integrate features such as authentication, analytics, and database CRUD operations. Live: https://lnkd.in/dCGFCiH5 Github: https://lnkd.in/dWpHgc4y Pathway to Tech Event 2: Here's My Key Takeaways: Dennis Crowley: Founder of Foursquare ($150M Revenue) When asked about the ideal tech stack, He emphasized the importance of being "willing to fill in gaps." It's not just about knowing specific technologies but being able to and ready to learn. His experience on failures "People quit on themselves or quit on their startup.", reminding me to stay resilient and never quit Tariq Afaq: First Engineer at AppLovin ($30Bn IPO) Tariq's talk was packed with valuable information. when he mentioned that this field is more than just coding, like being an engineer we can solve problems under pressure and get things back on track He also mentioned that you don't need to be super intelligent to succeed. Instead, focus on creating in-depth products, being quick and responsive, and working hard. Julian Alvarez: Ex-Meta, CEO of Wisdolia ($20K+ MRR) The most energetic speaker at this event! , His thoughts on how startup founders stick to their ideas rather than believing in their team's capabilities become the reason for their failure something exceptional and new for me to learn. His startup Wisdolia— is truly something. It generates flashcards for you from any YouTube video, blog, article, or PDF. I can already see it becoming a vital part of my learning routine! Hamza Ali - CEO of Olostep I was deeply inspired by Hamza Ali's vision for Olostep, which is enabling APIs to interact with the web as humans do. It's truly a brilliant idea that showcases his commitment to shaping the future of tech. 🔗 Here's the link to the recording: https://lnkd.in/dzX6Saaz

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New iterative reasoning technique could improve RAG app accuracy by 50% (vs. Naive RAG)! Another solid example of the rapid innovation cycle on RAG research. BTW, you can quickly find out answers to question like "Why did combining RAG with Fine-Tuning and Iterative Reasoning, such as OODA, improve accuracy by 50 percent?" in Epsilla (YC S23)'s "RAG Research Paper" smart search app at: https://lnkd.in/gVgzpbue , with number of research papers included exceeding 360. #genai #rag #smartsearch #innoation

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Fun fact: We built our GitHub Actions jobs and runners visualization for our own internal monitoring before we rolled it out to everyone. One of the particularly annoying things about GitHub Actions is the lack of visibility & control over the full end-to-end process. We don't control the webhooks. We don't control when the runner gets passed a job. We don't control the control plane of GitHub Actions. Sounds fun right? 🙂 It is, mostly. Until something breaks. Then it sucks as you have to figure out where things have broken. Most of the time, it's a lag on GitHub's end, either sending the webhook or sending the job down to a runner. But, it's not always easy to SEE that. So, we built an internal monitoring dashboard to monitor jobs getting allocated to online runners in a timely manner. This is eventually how we learned the lessons ☝️ Then we figured others would enjoy this view as well ✨ So we shipped V1 of our GitHub Actions visualization 🚀 This gives you a live look into the jobs and runners that Depot is managing across your GitHub organization. You can see queue times, job times, and the runners currently running.

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Learn the basics of how to build agentic AI products with this short course by Andrew Ng and Jerry Liu. DeepLearning.AI courses are easy to follow and serve as a fantastic starting point for developers who want to begin experimenting in the AI space.

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Every startup CEO should be using this. Meet your new AI SDR.

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Really excited about KIP-932 (Queues for #Kafka) and its impact on the AI world: massive worker architectures to index unstructured documents at scale, feeding LLMs. Combined to inference cost reduction, lower latency, and smaller specialized models: local #SLMs will be a game-changer for scaling AI workloads cost-effectively in the streaming paradigm. (SLM: Small Language Model)

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One of the simplest techniques for improving sensitivity in your experiments is eliminating or reducing dilution. Dilution is akin to throwing more hay in the haystack, thus making your ability to find a signal extremely challenging. In this blogpost, David Press and I explain dilution and provide some practical guidance on how to handle it. We also provide some examples showcasing how enormous is the impact from eliminating dilution. For ML applications, having a way to handle dilution can lead to 100x+ sensitivity gain.

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Big thanks to Jillian Forde for inviting me to chat about my #YCombinator journey on #AWS-ON-AIR! Quick summary about our chat: 1. YC is a game-changer for first-time founders—think fewer rookie errors, faster product development, and sharper GTM strategies. Plus, it boosts your fundraising game. 2. YC isn’t just a three-month sprint; it’s a marathon with a lifetime network and friendship of fellow founders. 3. Heads up: snagging a spot in YC isn’t a golden ticket. It doesn’t guarantee a successful exit. Keep running! Check full podcast at https://lnkd.in/g2YJbSFw

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