Adele Li

Amazon brings in Covariant founders Abbeel, Chen, and Duan 🤖 Reverse acqui-hiring of one of the most experienced robotic manipulation teams in the industry. Pieter Abbeel (UC Berkeley), Peter Chen, and Rocky Duan founded Covariant in 2017 to solve real-world pick-and-place for items with high shape and size variability. Their software already runs in production warehouses handling complex manipulation tasks. This follows Amazon's Kiva Systems playbook — acquire the team, integrate the tech, scale it across the fulfillment network. The timing matters. Tesla and other robotics companies are competing hard for this exact talent pool. Abbeel's work in robot learning and reinforcement learning is foundational to the field. Now that expertise goes directly into the largest logistics operation on the planet. What gets interesting: Covariant had multiple customers. Amazon now controls that IP and those deployment learnings. The gap between companies with in-house robotics AI teams and those licensing external solutions just widened. Nvidia and others building foundation models for robotics face a tougher sell when customers see Amazon vertically integrating this capability. Who's next? The acqui-hire cycle for robotics AI talent is accelerating. #robotics #AI #logistics #automation

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Wispr Flow has raised $30M in Series A funding led by Menlo Ventures, with participation from New Enterprise Associates (NEA), 8VC, and tech leaders like Opal CEO Kenneth Schlenker, Pinterest founder Evan Sharp, Carta CEO Henry Ward, and Lindy CEO Flo Crivelli. CEO Tanay Kothari said investor interest surged as top venture firms began using Wispr Flow daily, drawn by its unique dictation interface and AI-powered productivity features. Ivan Mehta | TechCrunch https://lnkd.in/ggTdPD4k #AI #ArtificalIntelligence

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AI agents without memory are stateless, inefficient, and limited. That becomes even more important as enterprises move from single-agent workflows to multi-agent systems, where context needs to persist across agents, sessions, tools, and LLM vendors. Excited to join David Joy from Cockroach Labs on May 19th for a deep dive on architecting persistent memory for multi-agent systems. 🚀 Timely topic for us: Memori Labs just released its new agent-native memory infrastructure, which automatically structures memory from agent trace and execution - not just natural language conversation. That means agents can remember what they did, not only what they said. We’ll also be sharing some exciting demos and perks for those who attend. Join us Tuesday, May 19th at 10AM PT. Register here: https://lnkd.in/gxWfxAxh

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Thank you to Brian Gormley and The Wall Street Journal for including my perspective on Generate Biomedicines’ IPO. “Generate represents exactly where this industry should be heading - AI-driven optimization of what reaches the clinic should be table stakes. That said, the market will ultimately value these companies in their programs, not their AI platform.” Optimizing what gets into the clinic matters. The deeper paradigm shift, though, is using AI to truly model human biology and reshape development from end to end. That is when the economics and outcomes of drug development begin to change.

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Amp, a newly launched Menlo Park startup founded by Andreessen Horowitz partner Anjney Midha that pools AI computing power for startups, universities, and other organizations, raised a $1.3+ billion round from investors including Andreessen Horowitz and Y Combinator as well as unnamed cloud computing providers. https://lnkd.in/edjZj2Te

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🚀💡 #AIWeek: NVIDIA Start Up Panel This panel brought together founders and technical leaders who are building the next generation of AI driven health technologies. Moderated by Amit Bleiweiss, Senior Data Scientist at NVIDIA, the panel featured Dana Sinai, Vice President of AI at Laguna Health, Tomer Ben David, Co founder and CEO of Vortex Imaging, Eran Miller, Co Founder and Chief Business Officer of MNDL Bio, and Shahar Harel, Head of AI at Quris AI. Speakers shared insights from real world development, including model optimization, data challenges, and the role of powerful computing platforms in turning ideas into clinical impact. The conversation centered on how advanced computing accelerates product development, improves clinical workflows, and enables companies to push boundaries in imaging, diagnostics, and personalized care. The panel showcased the creativity and ambition driving the global health tech ecosystem. #AIWeek #NVIDIA #HealthTech #Startups #AIInnovation

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HIMSS is almost here, and I’m looking forward to catching up with so many of you. I'm especially looking forward to our session with UC San Diego Health. Karandeep Singh and Jeffrey Pan will showcase how they're using Notable's Platform and AI Agents to act as a critical workforce multiplier, transforming patient access, care operations, and RCM across the enterprise. Learn more about everything we have going on at HIMSS here: https://lnkd.in/gQifSd2A. And definitely come say hello if you're attending!

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Santa Cruz Works has announced a strategic partnership with Runpod, a leading GPU-first cloud provider, to empower early-stage AI startups with scalable computational resources. This collaboration aims to eliminate infrastructure complexities and enable founders to focus on innovation. The partnership provides startups in the Santa Cruz ecosystem instant access to high-performance GPU environments across eight global regions. Runpod's dynamic, pay-as-you-go model allows AI builders to train, fine-tune, and deploy models without significant upfront investments. @John Tran, COO of Santa Cruz Works, emphasized the critical importance of accessible infrastructure for developing world-class AI companies. By removing GPU access barriers, the partnership enables entrepreneurs to concentrate on building transformative AI technologies. Runpod's platform is already trusted by major AI innovators like Replit, Hugging Face, and OpenAI. Startups can leverage the infrastructure for diverse applications, including model inference, custom model fine-tuning, and intelligent workflow development. Zachary Gulsby from Runpod highlighted the partnership's potential to unlock Santa Cruz's deep AI talent and entrepreneurial energy. By providing scalable compute resources, they aim to accelerate the region's AI innovation ecosystem. This collaboration represents a significant step in building Santa Cruz Works' early-stage AI platform, positioning the region as an emerging hub for technological entrepreneurship.

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Astor (YC S25) has raised a $5M seed round to build an AI-powered investment advisor that gives anyone personalized portfolio guidance from their phone. The company was founded by Bruno Koba, ex-Nubank and a Stanford GSB graduate, along with Daniel Tulha Hochstetler, who was previously at Stripe. High-quality financial advice has long been gated behind $5k–$10k/year minimums, leaving 150M+ Americans who invest with nothing but generic content, robo-advisors that manage but don't advise, or no guidance at all. Astor connects directly to users' brokerage accounts, scores portfolios on performance, risk, and diversification, and lets users ask any financial question via text or voice — all as a fully SEC-registered RIA. Congrats to Bruno, Daniel, and the team on the round! https://lnkd.in/d8qgu26M

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Axiom Math, a San Francisco-based startup developing a self-improving superintelligent reasoner, raised $64M in seed funding led by B Capital with participation from Greycroft, Madrona Venture Labs, and Menlo Ventures. Led by CEO Carina Hong, the company is beginning with an AI mathematician capable of solving complex problems, generating detailed proofs, and verifying its own work. The new capital will support Axiom Math’s operational expansion and further development of its technology. INVESTORS: B Capital, Greycroft, Madrona & Menlo Ventures ROUND: Seed AMOUNT: $64,000,000 HQ: #SanFrancisco #California #VentureCapital #AxiomMath #CarinaHong #BCapital #Greycroft #Madrona #MenloVentures #TradedVC

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In the latest episode of Lexicon by Interesting Engineering, Fernando Dominguez Pinuaga, VP at SandboxAQ, discusses how Large Quantitative Models (LQMs) are redefining the frontier of AI and quantum. Tune in to hear where AI + quantum are headed next. https://lnkd.in/g3W2m-fm

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Last week, our Founder and Managing Partner Lu Zhang attended GenAI Week SV 2025 in Santa Clara, where she shared insights on a panel titled "Inside the VC's Mind: What AI Founders Get Wrong About Fundraising." With infrastructure saturation, model commoditization, and agent fatigue shaping today's AI landscape, founders face an evolving set of challenges. The discussion explored what truly differentiates fundable AI startups today, from mastering effective go-to-market strategy and recognizing misleading signals to building genuine competitive advantages beyond the model layer. Great to share the stage with fellow investors Alvin Xiao (NYX Ventures), Kahini Shah (Obvious Ventures), Shannon McClenaghan (StartX), Prat M. (Xfund), and Jenny Xiao (Leonis Capital). The conversation was both insightful and engaging with this thoughtful group of investors. #AI #VC #StartupFundraising #AIStartups #FounderAdvice

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"Build the event you wish existed" That's what we at Monadical did last week at #NYTW. We wanted an AI Engineers discussion for Engineers. There's always a lot of events out there for VCs to network, or for startups to learn about G2M, but very little on lessons learned from actual engineers in the field. So that's the event we hosted. Big thank yous to our awesome panel, Roy Pereira, Ben Cohen and Corey J. Gallon. Here's the key takeaways and the AI tools we're using. 🚀 All three panelists independently called AI Agents the most transformative LLM application they’ve used. They specifically called out Claude 3.5 Sonnet for its accuracy and reliability. 🪨 We dug into how LLMs are “jagged”, not general. They can be shockingly good at some tasks and completely fail at others. Everyone agreed: good evaluations are critical (and hard.) 🧪 Corey noted how public benchmarks and reality are two different things. Most public evals are saturated or gamed. ♊ Ben emphasized that AI projects are actually two projects: building the tool and building the evaluation process. 🧱 We explored how falling dev costs may impact startup defensibility and labor demand. Roy shared that founders are already shifting strategies in response. ⚒️ In a world of daily AI launches, the panel discussed how they decide what’s worth attention, and what’s just noise. They called out tools like Goose, Aider, Claude Code, and Monadical’s own Cubbi, which helps run agentic workflows safely in dev environments. (links in the comments). CTA: What would you want to hear in an AI Applied Engineering talk you attended?

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