Hunter Brooks

Thrilled to share that Lume (YC W23) has raised a $4.2M Seed Round led by General Catalyst! This journey began with a question that nagged at me every time I faced it as an engineer: Why is data mapping still so painstakingly manual? In an era where technology evolves at lightning speed, the process of moving data between systems remained stuck in the past. It was a problem that not only I faced but one that has persisted for decades. So, we decided to tackle it head-on. At Lume, we're reimagining data integration. Our AI-driven platform transforms days of manual data mapping into mere minutes. Whether it's ingesting customer data, normalizing API responses, or mapping complex taxonomies, we're making seamless data translation a reality. I'm incredibly honored to be on this journey with some of the brightest minds I know: Nicolas Machado, Robert Ross, and Collin Montag. And we're just getting started... If you're an engineer looking to tackle difficult problems, please reach out! A huge thank you to our amazing partners who believe in our vision: Puneet Kumar and Brad Flora from Y Combinator, Quentin Clark and Max Rimpel from General Catalyst, Vinod Khosla from Khosla Ventures, Mike Maples, Jr. from Floodgate, Nikhita Jaaswal and Fouad Farhat at Soma Capital, Sabrina Hahn, Devvret Rishi, Sam Stone, Ana Clara Martins, Sigalit Perelson Scharfstein, John Bautista, and others! Read more about the announcement in the TechCrunch exclusive (in the comments). Thank you, Rebecca Szkutak for the feature! 👇

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I believe in the same future Mark discussed on Cleo Abram's podcast. The reality, though, is a future where "every company will have multiple internal AI systems" doesn't mean those companies will be building their own systems from scratch. This is why making Basewell's model more accessible both inside and outside of our platform is so critical: because modern companies deserve contextualized, accurate, and fast knowledge/enablement systems actually built for how people learn and work today. (Even more critical when companies can implement said systems without needing to hire new talent or overload their existing teams.) Building enabled teams is a problem as old as time. Yet most enablement systems use bloated, outdated standards, forcing companies to move slowly, waste money by hiring more people, and create inefficient, redundant workflows that hurt the entire organization. Current tools were built for a world that hadn't changed yet. It's not possible to have a forward-thinking organization living in a world where "every company will have its own AI" without ensuring your tools won't bottleneck your progress. Will share more soon.

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Very excited that VitalStage Ventures is a small part of Groq’s new round of funding. We are all-in on AI infrastructure as the picks and shovels enabling this new generation of innovation. With respect to Groq, we particularly love their new hardware + software approach to accelerating AI inference. Just try out Groq.com and you can sample what the fuss is about. Having specialized Language Processing Units (LPUs) for inference enables dramatic performance gains at higher efficiency with less thermal impact. And now by hosting models via GroqCloud, Groq lowers the barriers for teams to be able to leverage many models without having to set up and deploy their own AI infrastructure. #ai #groq #ainative https://lnkd.in/gcEcXfme

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Magic, a U.S.-based startup developing AI models for software writing, is reportedly in discussions to raise over $200 million in a new funding round. This round is expected to value the company at $1.5 billion, a significant increase from its previous valuation of $500 million in February. This potential investment highlights the growing interest in AI-powered coding tools, which are seen as a way to potentially reduce costs and increase efficiency in software development. However, the high valuation for a pre-revenue company also underscores the speculative nature of investments in this rapidly evolving field of AI technology. ➜ Check the news at: https://lnkd.in/d2Sj_TbA ➜ Vendorvise's official Instagram: https://lnkd.in/ebK2KQ2C ➜ Vendorvise's Linktree: https://lnkd.in/dQdbMdth 🤖 If you enjoy reading my posts about AI and tech news, hit the like button and share with your friends to support my content! #ai #artificialintelligence #ainews #aipowered #news #blog #magic #software #coding #tools #funding #200million #valuation #vcs #us #generativeai #aitech #technology #content #socialmedia #future #new #business #techtrends #innovation #launch #success #markets #marketing #people #industry

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📜 A new blog post explaining the fundamentals of RL for LLMs—the perfect place to intuitively understand PPO and RLHF from first principles. 👇👇 Pre-trained LLMs are often compared to Lovecraft's Shoggoth, a monstrous, shape-shifting beast. PPO is the algorithm that brought it under control. Take a look! 🔗 https://lnkd.in/eXqDvrUV

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AI Innovation Taking Center Stage The recent news of /dev/agents raising a staggering $56M seed round at a $500M valuation is a testament to the transformative potential of AI-driven developer productivity tools. This massive funding round highlights: -The growing demand for AI agents that streamline workflows, enhance efficiency, and supercharge development teams. -How investors are betting big on technologies that redefine traditional software development processes. As someone passionate about leveraging AI for impact, this news reinforces the importance of continuous innovation. Tools like these aren’t just about productivity—they’re shaping how the world builds technology. Kudos to the /dev/agents team for this milestone! What are your thoughts on the future of AI in development? #AI #StartupFunding #Innovation #TechTrends https://lnkd.in/gXnd5DaB

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Y Combinator（YC）のRequest for Startupsについてまとめた記事の第1弾をnoteに投稿しました。アクセラレーターとして多くのスタートアップを育ててきたYCが、応募してくるスタートアップに対して立ち上げてほしいアイデアを募集している要件をまとめています。Y CombinatorのRequest for Startupsは、今後注目される領域や技術・サービスが現在不足している点を考える上で、一つの指標として非常に参考になる内容と思います。 ブログ記事はこちら（Here is the blog post）↓ https://lnkd.in/gMicj2Jp *Although the articles are in Japanese, please feel free to contact me in English if you are interested in the content. I have posted the first article summarizing Y Combinator's (YC) Request for Startups on note. As an accelerator that has supported many startups, YC has outlined the ideas they want incoming startups to develop. Y Combinator's Request for Startups serves as a valuable indicator for understanding the areas, technologies, and services that are currently lacking and will be in the spotlight in the future.

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The promise(s) of #DeepTech startups are appealing to many investors... But do they provide superior returns? To examine this thesis, we took a deep dive into Intel Ignite’s portfolio (Israel), known for its #DeepTech affiliation in the last 4 years. *Including the latest batch (#9). 56 companies (+2 in stealth)... Ready? Let’s go! Most recurring investors? Kmehin, NFX, toDay.Ventures, TLV Partners. 2 companies are inactive and 7 companies have been acquired (nice Eli!), some by other Israeli companies like Check Point Software & Snyk (Atmosec (Acquired by Check Point), Helios (part of Snyk). Pretty incredible stat considering the short time most these companies have been around. *Excluding them from my analysis going forward. Company sizes by headcount:  🥚 Small (0-15) - 23, 48.94%. 🐣 Medium (16 - 35) - 16, 34.04%. 🐥 Large (36+) - 8, 17.02%. Fastest growing companies YoY in employees for each category: 🥇Filo Systems (Small). 🥇Pelanor (Medium). 🥇Exodigo (Large). 💵 Zesty leads the list with the most funding to-date, totaling $117M raised, just a tad above Exodigo with $116M. 💚 18 companies, 38.3%, disclosed funding in the last 12 months.  💛 16 companies, 34%, haven’t disclosed new funding in 12-24 months.  🧡 13 companies, 27.7 haven’t disclosed new funding in 24+ months. Honestly, this time most of the portcos are stacked with fresh funding compared to other portfolios I review. Impressive given that the local market is just starting to pick up again. ARR (beta, working with the ‘lower end’ estimation): 📈 4 companies are at $5M+ / ARR 📊 8 companies are at $2M+ / ARR 💹 10 companies are at $1M+ / ARR 🏗 25 companies are either below $1M ARR or have no estimate at this point. Want to know who? Perform your own analysis? Check out the free full list through Dealigence in the link here -> https://lnkd.in/dh58eXjt If you liked this post, kindly click follow 🔔 and send it to friends who would find this interesting 😋?   P.S - No one at Intel Ignite asked me to do this. I simply heard great things from David & Ohad, both program alums from LayerX Security and Hyperspace and decided to quench my curiosity 🙂. P.S #2 - Both David & Ohad lead incredible companies and you should definitely check them out. Don't take my word for it, see the data yourself in the platform. Gil, Yaniv 😎

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2025 tech areas to be covered by new startups by Andreessen Horowitz #startups #technology #2025 #ai #software #bio #health #crypto #enterprise #games #infrastructure

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Highly recommend this interview from the All-In Podcast summit with Tekedra N. Mawakana, Co-CEO of Waymo. Great work by Jason Calacanis, Chamath Palihapitiya, David O. Sacks, and David Friedberg. Here are some insights that stood out to me: 🚦 Why does Waymo avoid freeways? Freeways are pretty straightforward and Waymo is more focused on denser, unpredictable environments since they help the AI learn faster and better. 🤖 Tekedra referenced the ‘Waymo Driver’ often, which is an interesting term - in a way, they are building ‘one new driver’. 🤝 Will Waymo disrupt and decimate Uber? Well they’re partners so it would be an awkward yes so take this one with a grain of salt. Tekedra said that they don’t want to be experts at everything. They partner with OEMS on the vehicle side, so it made sense to partner with Uber on the rideshare platform side. I buy that.

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Excited to share our 0-1 #DevGTM Playbook for early-stage technical founders building developer tools and infrastructure! We at Speciale Invest had the privilege of working closely with many brilliant technical founders and evaluating many Devtools/Infra Cos. During our in-depth discussions, we discovered a recurring obstacle that many of these technical founders face: despite identifying problem statements and developing cutting-edge technology but crafting a clear and effective GTM strategy often proves to be a significant challenge. Recognizing this gap, we set out to create a comprehensive playbook tailored for early-stage technical builder/founders in their 0-1 journey. My colleague Aryan Pareek and I have spoken to over 50+ #DevTool founders, GTM experts, and #developers from companies like Amnic, Appsmith, DhiWise, Dyte, Esper,Hashnode,Hivel,Keploy 🐰, LambdaTest, Neverinstall, Portkey, Reo.Dev, Requestly (YC W22), ToolJet, Tailcall, Typo, Unstract , videosdk.live, Zenduty and many more. And we consolidated the best examples and learnings into our playbook. We dive deep into various aspects of #developer GTM, including defining your ICP, buyer journeys, messaging for developers, #SEO, content strategy, and more - all tailored for dev founders. Check out the playbook here: https://lnkd.in/g425vuqy Huge thanks to all the #devfounders and #GTMExperts who shared their invaluable insights and experiences with us. Special shoutout to Dev founders and all the amazing developers and GTM experts who gave us their valuable time. 🙏 📣 Special Creds to the devfounders who helped us with this: Sachin Jain Achintya Gupta Navaneeth Padanna Kalathil Vishal Virani Anirudh Murali Shiv Sundar Kshitij Mohan Sudheer Bandaru Venkatesh Radhakrishnan Harini Janakiraman Arjun Kava Narendran Hariparanthaman Sidhant Goyal Madhukar Kumar and many more.... (lol - I've exceeded the maximum mention limit) Special thanks to Freshboost for assisting us with SEO strategies. *Please tag technical founders/builders who would find this useful, and feel free to share your feedback with us over DM* P.S.: It's still a work in progress, and we'd love to hear from more technical founders about your experiences and challenges about your GTM journey. Your feedback will be invaluable in making this resource even better for the broader dev ecosystem. Arjun Rao Vishesh Rajaram #TheDeepTechVC — Build from India for the World

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Together with Robert Chandler, we're at the Y Combinator retreat and excited to show you something 👀 Today on Product Hunt, we’re launching our open-source Wordware (YC S24) project - Audioscribe, an AI tool that structures your thoughts into simple notes with an entire LLM backend built on Wordware. Just press record and that’s it. No login. No credit card. Please give us an upvote if you can! 🙌🏻 Why are we launching this product? To better showcase the possibilities of Wordware. Use-cases are practically infinite—we have customers who are lawyers, marketers, construction engineers, and even radiologists. In general, it’s a modern wave of builders who want to make use of AI in their jobs and lives. While Wordware serves as an LLM backend for numerous applications and some AI-first startups, as well as a prototyping tool for enterprises, we can’t publicly share our customers’ work. We’ll keep building more to demonstrate what you can do and open-source every project to make it easy to start. PS: Remember that Audioscribe is a WordApp—a Wordware application. Our IDE, Wordware, lets you build AI apps using natural language. That’s why we call them WordApps—you create them with words (pun intended). You can start by duplicating the LLM-backend for Audioscribe or build from scratch. Give it a try and let us know what you think! Fun fact: Initially, we built this as an internal tool because I often talk to myself to brainstorm and organize thoughts, and all of the existing tools were simply not good enough. I needed a different structure, different prompting, and through a chain of prompts on Wordware, I was able to easily achieve satisfying results, and then save it to Notion.

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Why is a (minimum) 40 second load time for AI models a problem? The 40+ second load time (in practice closer to many minutes for medium-sized models) cause issues like: - Higher costs: You pay for the 40+ seconds of precious GPU time- optimized AI inference goes to waste when you pay even more to load the models. - Over-provisioning: You need to plan ahead for the 40+ second lead time when scaling up your GPU count with demand- causing you to acquire too many GPUs. - Developer inefficiency: Every time you fix a runtime issue in Python, you wait 40+ seconds for the next run to invoke. Why can't we pre-load the models into memory and spin-up an inference process separately? The 40+ second load time don't seem substantial at first but compounds in terms of both money lost and innovation lost. At Outerport we are working on technology to make it easy to use 'memory as storage' for your AI models and tensors across distributed processes. Thanks Rajeev Chand for the shout out!

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Watching YC's Fall '24 batch, we're seeing a fundamental transformation in how companies scale. A few key observations: Development cycles are compressing. In F24, a developer tool reached $102K ARR within three weeks of launch. This isn't an outlier either, in the batch we also saw examples of... $655K ARR, growing >10% week-over-week $1.6M ARR, growing 23% month-over-month $670K ARR in 2 months Capital Efficiency will be the new normal as the traditional startup playbook is being rewritten: Zapier (YC S12): Reached hundreds of millions in ARR after only seed funding Baubap (YC S21): Achieved $100M+ revenue and profitability with single seed round SoloSuit (YC W21): Showing similar capital-efficient growth trajectory 🔄 Why This Matters... - Seed rounds might become the dominant form of venture capital (as Chamath recently noted on All-In) - The 18-24 month seed-to-Series A timeline is compressing - Companies can reach $1M+ ARR with small teams and minimal capital The new challenge is... Speed to defensibility > Speed to market With lower barriers to entry, competitive advantages must be built faster. The winners aren't just those who get there first, but those who build lasting moats quickly.

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The biggest reason for churn off AI products is that they lack accuracy or reliability. You can fix that problem for RAG applications in one line of code with Pongo's semantic filter. On a benchmark of 100 questions from Airbnb's 2023 10-k, we improved top 3 accuracy by 40% over OpenAI embedding vector search. Try 500 queries free -> https://joinpongo.com/ Benchmark results -> https://lnkd.in/gaStUZgq

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Where did they get that Carpet. I want a startup that sells solely those carpets online. Let's call it CarpetWorld.ai (name is available) https://lnkd.in/g_WRA6-m The AI looks at your room, and shows you a bunch of carpets that you can order with one simple click. Every 6 months, you get a new carpet in the mail. Somebody comes by from TaskRabbit, arranges everything, new paintings. You feel like you're in a new home. They don't even knock. They just come in. From the profits off selling the carpets, we make a better Search Engine called Magic CPT (carpet), homage to our time selling carpets. #ai #ideas

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We have the largest database of LLM API pricing at Helicone (YC W23) with over 300+ models! 🚀 And it's now fully open-sourced! We've launched a free LLM API Pricing Calculator that lets you compare costs across various models and providers like OpenAI, Anthropic, and more—all in one place. 📌 Link in the comments

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The major areas of AI innovation automate white-collar work. Reviewing the BLS’ data on employment for white collar work, I aggregated the data to these categories. It’s striking that most of them already have a significant number of AI startups pursuing their ambitions to change workflows. Software engineers were the first to benefit with Copilot. Today, there’s a panoply of different kinds of AI software for developers, including test generation, code refactoring, code generation, & security analysis. Within education, The promise of computer adaptive testing and an individualized tutor and the style of Alexander the Great & Aristotle is possible. Automated document ingestion & reconciliation for closing books is changing accounting. AI powered financial due diligence rips through public filings, private placement memoranda, & compliance automation. Legaltech has surged automating demand letters for personal injury, writing briefs for attorneys, & chomping away paralegal work. We could keep iterating through the list. But if a founder wanted a list of jobs to automate, the BLS’ white collar jobs boards is a wonderful place to start. AI will change these workflows & capture a meaningful fraction of the labor spend. It’s a roadmap for the White Collar Revolution.

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