LAB News & Signals

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Getting funds into LAB shouldn't be a side quest Use Google Pay to top up your balance and get straight to business Apple Pay for iOS users. Coming soon 🔔

10/100·CNeutral+1

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Chromia’s website also has a brand new design: ➤ https://chromia.com/ We’re actively exploring and building applications to make Chromia the secure data layer for AI agents. We’d love to hear your feedback! https://x.com/Chromia/status/2113517274699289028 Quoted @Chromia: Our revamped sites are live! AI Lab - https://www.evalengine.ai/ decenchro - https://decenchro.com/ More updates coming soon 🔥

35/100·CLong

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AI Semis Trade: From Arousal to Reality The past few weeks have been painful for AI semi investors. One of our mistakes early in the month was not realizing how much of an impact Anthropic’s ARR print would have on the AI trade, and not “sussing” out the set up heading in: lower distillation revs, OpenAI taking share in September, & META/MSFT off-ramps. These were all things that were reported on; if this was an earnings print, we wouldn’t have wanted to be long in the weeks heading into it. In hindsight — knowing what we know now, it was a perfect set up to reduce exposure into it. The upside of whiffing on that trade and the market’s renewed focus on Lab ARRs and financing? It has forced me (and other investors) to sharpen our pencils and better understand the different moving pieces of the trade, and how they play off each other. Let’s rewind a bit before diving into where we are now: For the first three years of the AI semi trade, and especially during the May/June go-go days, investors were in the throes of the honeymoon phase: maximum arousal, minimum scrutiny. Every piece of news was looked at with rose-colored-glasses. It’s just like the beginning of a new relationship when the infatuation is so strong that your partner can do no wrong. Even when she tells you she believes in an "open-source relationship," you somehow hand-wave it away and convince yourself it’s just going to soak up more of the frontier labs' excess demand. When your level-headed friends pull you aside to point out glaring red flags, like the fact that she’s running a shadowy circular-financing scheme with her roommates, you don’t listen; you just stop inviting them to parties. Before you know it, you’ve turned on Gavin Baker’s X notifications and forward SemiAnalysis to anyone who thinks you’re moving too fast, the ultimate wingmen who never stop hyping her up and telling you what you want to hear. “It’s way bigger than just coding, bro. She’s going to replace the entire global labor force.” Before long, the endorphins and dopamine completely take the wheel. Even if you carry the scars from past relationships — whether the early 2000s, GFC, 2019 SaaS, or the 2020–2022 Covid binge — the blinders go right back on. Those exes weren’t real supercycles and everyone knows there’s no dark fiber in GPUs, you tell yourself as you stare at GPU rental prices. You’ve even picked out baby names: Bel if it’s a girl; Claude if it’s a boy. But eventually the dopamine wears off, and you have to get to know the person you’ve been telling everyone is perfect. You begin to see the flaws and start asking practical questions about spending habits, expectations, whose money is actually paying the bills. Can we afford this lifestyle on those lab ARRs, or are we just annualizing the honeymoon and assuming the capital stays cheap forever? And is there enough power in ’28 to keep the spark alive? Things suddenly feel a lot more complicated, and we feel some investors longing for the simpler, more intoxicating days of May and June. But we see the end of the honeymoon as a chance for the relationship to mature. That means accepting where we are, adjusting expectations, and focusing our attention on where the strengths are rather than the flaws... Retweeted by @jukan05 from @TMTBreakout(Historical earnings: For fiscal 2026Q3 (period ended 2026-03-31), Microsoft reported basic EPS of 13.19 and diluted EPS of 13.14, with net income of USD 97.983 billion, versus basic EPS of 10.03, diluted EPS of 9.99, and net income of USD 74.599 billion in the prior-year period. In the preceding quarter (2026Q2, period ended 2025-12-31), basic EPS was 8.91, diluted EPS 8.87, and net income USD 66.205 billion. Consensus expectations: For the upcoming 2027Q1 event on 2026-10-28, consensus EPS estimate is 4.7184 and revenue estimate is USD 90.707 billion.)

25/100·CNeutral+10

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More reference control. Fewer denoising steps. More places to run H3. The latest community contributions span 8-step reference-conditioned video + audio, 4-step distillation, sparse attention, and reference-token compression - alongside serving and workflow integrations across GPU servers, TPUs, and Apple Silicon. What matters is what this enables: more affordable experimentation, finer creative control, and more choices about where and how video generation runs. Open models become more useful when the community can improve the methods, adapt the runtime, and build workflows around them. Credit to @haoailab @yisun0618 @lanfeng491270 @guocheng_qian @Alissonerdx @ddalcu @tazmannner @HaochengXiUCB @huggingface @Jhuaplin, and the PTD, DMAD, SparkH3, TorchTPU and FlashML teams - including Zhengming Yu and zechengtang on GitHub. 11 additions to the H3 ecosystem index. Thank you to everyone building, testing, and sharing. https://github.com/MiniMax-AI/awesome-minimax-h3-integration Quoted @MiniMax_AI: Open weights. Shared progress. MiniMax H3 is moving fast. We built H3 for video generation with native stereo audio and multimodal reference control. The open-source community is making that capability faster, more accessible, and easier to build on. Recent highlights: • FastH3 — FastVideo, Nuva Lab and NVIDIA: 4-step distillation, now running on DGX Spark and Apple Silicon. • Sol-H3 — NVIDIA’s SANA team: 15 seconds of 768p video + audio in 6.6 seconds on 8×B300, in the team’s warm-inference benchmark.* • VDN — Haocheng Xi and the OpenVDN team: rethinking attention for faster H3 inference, with weights, training and inference code released. • PDD — NVIDIA’s distillation method, brought to H3 by Alibaba PAI as 8-step Acc-LoRAs, now supported in ComfyUI. • LightX2V — 4- and 8-step Turbo LoRAs, with workflows for text, image and reference-conditioned video + audio. Behind every release are people training, optimizing, quantizing, testing and sharing. Special thanks to: @haoailab @nuvalab @NVIDIAAI @xieenze_jr @HaochengXiUCB @ArashVahdat @julberner @LightX2V @ComfyUI And to the individual contributors pushing the work forward: @haozhangml @cxlcl1 @lawrence_cjs @yitongli165665 @haopengl33 @songhan_mit @shanasaimoe Thank you for building with H3 and helping make it faster, more accessible, and more useful for the community. Powerful models go further when we build together. Keep pushing H3. Excited to see what comes next. 🚀 Explore the ecosystem: https://github.com/MiniMax-AI/awesome-minimax-h3-integration(Historical earnings: For fiscal 2026Q1 (period ended 2026-03-28), Intel reported basic and diluted EPS of -0.73 and net income of USD -3.728 billion, compared with basic and diluted EPS of -0.19 and net income of USD -0.821 billion in the prior-year 2026Q1 period (ended 2025-03-29). For full-year 2025 (ended 2025-12-27), basic and diluted EPS were -0.06 and net income was USD -0.267 billion, versus basic and diluted EPS of -4.38 and net income of USD -18.756 billion in full-year 2024. Consensus expectations: For the upcoming 2026Q3 event on 2026-10-29, consensus EPS is 0.3945 and consensus revenue is USD 16.447 billion.)

20/100·CNeutral+14

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THE BLOCK: A researcher published 11 unpatched flaws in VPN service Tailscale, arguing that “infrastructure is vulnerable today.” In lab tests, a user with approved Tailscale SSH access could gain root access and spread to other devices on the network. Tailscale has not yet issued a fix. Tailscale is a VPN service, built on WireGuard, that people use to log into their own computers and servers from anywhere. Umbrel, a home server platform used to run bitcoin nodes, calls it “the easiest way” to reach an Umbrel remotely in its support docs. Erica Windisch of Cyberdione Labs ran the tests between Oct. 22 and 24 on Tailscale’s latest client. Her report, linked below, says to turn off SSH forwarding for now. Tailscale VP of Engineering Mike Shaver said on Reddit that the company has received the report and is “not recommending that everyone disable Tailscale SSH.” He said the issues concern what happens after someone is authorized to connect, which “isn’t the same as an unauthenticated attacker being able to connect to arbitrary machines.” In a reply, Shaver confirmed the flaws affect Tailscale’s own SSH feature, not regular SSH run over a Tailscale connection. Tailscale plans to publish a security advisory with patches.

15/100·CNeutral

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This Week in Virtuals: Native Pearl, Private Payments, and Derive Options for Agents px402 keeps an agent’s address off every x402 @USDC payment. Butler hedges BTC and ETH on @DeriveXYZ, buys native Pearl on @prlnet, copies traders and reprices farms on rule changes. Here’s what shipped: VIRTUALS 🟩 Native Pearl, served on a silver platter: tell Butler how much you want, and it handles every step to deliver native Pearl to your own wallet after one approval. No exchange account, no bridge to run. 🟩 Derive options on autopilot: your BTC and ETH, covered on @DeriveXYZ before every Fed, CPI and jobs release. Tell Butler the drop you can take, and it does the rest after one approval. No calendar, no options math. 🟩 Cross-chain copy trading: tell Butler which traders to follow on X, @fomo, @pumpfun and more. It pulls their wallets together, tracks every move and keeps copying their trades across chains, all inside the limit you set. 🟩 Rule-aware trading: when a protocol changes its rules, Butler reads the change, the team behind it and the conversation on X, checks it against what’s onchain and reprices your position within minutes, without being asked. Starting with Papertrade’s PAPER. 🟩 @eastworlds_io, Virtuals’ robotics data and deployment lab, took part in the global stress test behind @dreamlabs_ai’s Dream-1 launch ECOSYSTEM 🟩 @PRXVTai made private agent payments live on Virtuals Protocol with px402, a privacy layer for x402 that keeps an agent’s address off every payment while merchants still get paid in USDC. 🟩 @Mute_swap added new features that let you get Monero or Zcash instantly on its platform, as it builds the privacy layer for the Virtuals agent ecosystem. 🟩 @itsovercall launched mainnet on Robinhood Chain, with 2,422 positions from 109 players in its first 4 days. Stakers now earn 25% of platform fees paid in its token, and Overcall is listed on @DefiLlama. 🟩 @LighthouseWeb3 raised more strategic funding for a $1.58M total and made Lighthouse Memory payable in its token, with one memory shared across Claude Code, Codex and Cursor. 🟩 @reppo launched Loop in public beta, updating Eval API scores every few seconds instead of a one-off check, and added x402 so any agent can pay for evals on demand. 🟩 @ProjectVEXai put VEX on Cloud into internal testing with off-chain trading and up to 60 days of autonomy, as its agents passed $3.5M in real trading volume. 🟩 @ethy_agent previewed Strategy Lab, the core of its V3 upgrade, for building, backtesting and deploying strategies through chat, coming in Q4. 🟩 @sibyl_labs_ made Sibyl Memory Pro team billing live, so admins can add or remove users with billing adjusting automatically, and its self-learning keeps entities like companies and people up to date. 🟩 @RatehopperAI now supports @aeroxyz, so agents can provide liquidity to Aerodrome pools, automatically choosing the protocol with the highest earning potential. 🟩 @wardenprotocol raised Token Terminal agent limits to $25,000 a day, lets hands-free trading run up to 30 days, and marks agent trades more clearly in your trade history. 🟩 @myrad_hq added Sports as its fourth image category after 300+ users uploaded images in a week, with 4,000+ new users joining in the past month. 🟩 @grid_arena now offers 81 markets with up to 40x leverage, all in one place, with many more markets coming soon. 🟩 @WizzHQ opened the waitlist for @velocityosxyz, its agent that trades for you based on charts, social sentiment and market trends. 🟩 @xmaquina’s DAO passed BOT-15 with 88% approval and 34M+ votes for a strategic allocation in @SkildAI, and portfolio company @NEURARobotics unveiled 4NE1 Gen 4, built for series production.(Historical earnings: For 2026Q1 (period ended 2026-03-31), Robinhood reported basic EPS of 0.39, diluted EPS of 0.38, net income of USD 0.350 billion, and revenue of USD 1.067 billion, versus basic EPS 0.38, diluted EPS 0.37, net income USD 0.336 billion, and revenue USD 0.927 billion in the prior-year period. For full-year 2025 (period ended 2025-12-31), basic EPS was 2.12, diluted EPS 2.05, net income USD 1.883 billion, and revenue USD 4.473 billion. Consensus expectations: Consensus for 2026Q3 (event date 2026-10-27) expects EPS of 0.5548 and revenue of USD 1.431 billion.)

15/100·CNeutral+25

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There’s a really pronounced divide between people who are on the AI side of things and people who are on the biology side of things. Even among people working in AI, the divide persists based on where they’re focused. The AI side, adherents of scaling laws and the bitter lesson, believe that AI getting better means AI being more capable of novel discoveries in medicine (that go beyond discovering new drugs in well understood targets or speeding up dry lab work etc). The biology people think the idea of a bitter lesson in biology is kind of ridiculous and that regardless of AI’s capabilities it’s going to be at least 5-10 years until you could hope to reliably simulate human toxicology in silico (right now AI/ML can’t even reliably simulate in vivo studies like binding affinities or functional assays). Even the most AI pilled of them, who will list all the areas that AI can reduce the time spent on various areas, don’t think the concept of AI discovering novel targets or generating new understanding of causal biology is realistic in the near term. Most, in fact, will readily characterize the assumption that even an “ASI” level model could find cures hidden in our current understanding (without expanding that understanding with significantly more biological data) as patently false. This was a big part of why we wanted to experience it ourselves by using AI for a (very) small portion of what it can do in biology. It was both mind blowing and revealed some poignant insights into how different the problem of making AI better at something like coding is to the problems of biology. Even if it unlocked the ability to generate new molecules at a stunning pace, its simulation (in silico) of binding only had 49% accuracy. And if we wanted to improve that, we’d need to feed it back the data from the lab - data that took about 30x as long to get as it took to generate the molecules. And these were tests in a test tube (turn of phrase), imagine how long it would take if we wanted to improve the model with data that required recruiting humans and monitoring their reactions. Human biology is very complex, and adding a drug - especially a novel drug and doubly so for a novel drug acting on a novel mechanism - means mapping interactions that have nth-order-effects that we don’t have the data to predict. Virtual cells have made advancements enabled by AI, but the perturbations equate to a small fraction of the possible. This is before you even get into curing disease, especially uniquely human diseases. Brain function involves cellular identities that are unique to humans, meaning animal studies are of little use. How long does it take to understand what the side effects of chronic administration of a drug in humans are? AI can speed up analyzing the data, or designing the trial or even getting it approved…but it can’t make a 6 month trial complete in 3 months. I think its important to point out that significant advancements can be made in AI that contribute to biology, while also being realistic about how much it speeds up something as complex as curing a specific cancer or diseases of the brain. Retweeted by @jukan05 from @citrini

5/100·CNeutral+4

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JUST IN: UK partners with OpenAI, Anthropic, and Google to launch AI lab focused on preventing biological threats

20/100·CNeutral

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https://t.co/wH0ZATZ1Nw Retweeted by @MidnightNtwrk from @atrium_lab

10/100·CNeutral

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JUST IN: UK unveils new AI biosecurity lab supported by OpenAI, Anthropic, & Google DeepMind, with up to £200 million in AI model credits to help combat biological threats.

35/100·CLong

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@OpenAI @lightspeedvp Thanks John! Looking forward to more together. Reply to @johncumbers: @kevinweil left @OpenAI to build a chemistry lab. That tells you where the real bottleneck in AI drug discovery is. Warp Sciences came out of stealth this week with $215M to build a US-based chemistry CRO that pairs experienced chemists with AI and robotics. @lightspeedvp led, with @ivp, @mayfield_fund, @Lux_Capital, Premji Invest and @MenloVentures in the round. I know Kevin and @dpatil well. This is the team I'd want on this problem. Designing a molecule is getting easier. Making it, testing it and learning from the result is still slow, manual and mostly offshore. Warp is going after that physical loop. What stands out to me: - They start with lead optimization analog synthesis. Real compounds delivered to real customers. - They charge per compound delivered. If the synthesis fails, the customer doesn't pay. - They record failed experiments too, and run their own campaigns to generate training data. - Customers own their programs. Warp has no pipeline of its own. - It's built in the US. The founders: - Kevin Weil (CEO), former CPO and VP of Science at OpenAI - DJ Patil (COO), first US Chief Data Scientist - Sol Reisberg (CSO), medicinal chemistry leader from Terremoto Biosciences - Mano Paluri (CTO), founding member of FAIR and VP at @Meta Superintelligence Labs This round also lands in a soft market. Biopharma VC fell to $6.44B in Q3 from $10.17B in Q2. Investors are still writing big checks for teams that tie AI to the lab bench. We talk about this every year at @SynBioBeta. The companies that close the loop between models and wet lab work will move fastest. Congratulations Kevin, DJ, Sol, Mano and the whole Warp team.

10/100·CNeutral+6

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YZi Labs Introduces Its First Atlas Scout Cohort to Back Student-Sourced Early-Stage Startups Key Takeaways YZi Labs is introducing the inaugural cohort of the Atlas Scout Program to give exceptional university students hands-on exposure to early-stage investing earlier than the traditional internship, analyst and associate path. Scouts will source deals, conduct initial research and diligence, build conviction and may help support early-stage founders across Web3, AI and biotech, with up to $1 million in indicative allocation to opportunities arising from the Program and access to YZi Labs' 300+ portfolio ecosystem. The first cohort brings together four Scouts from Stanford, Yale, UC Berkeley and UCLA, with backgrounds spanning applied mathematics, AI and physical AI, neuroscience and biotech, AI infrastructure and agents, computational biology and neurotechnology. YZi Labs is introducing the inaugural cohort of its Atlas Scout Program, bringing four university students from Stanford, Yale, UC Berkeley and UCLA into its early-stage investment work across Web3, AI and biotech. Atlas gives students the autonomy to launch initiatives on their campuses – from building founder communities to exploring investment opportunities. Students source founders, conduct diligence and develop their own investment perspectives alongside the YZi Labs team, with up to $1 million in indicative allocation to opportunities arising from the Program and access to YZi Labs’ 300+ portfolio ecosystem. YZi Labs has a belief that the industry needs to take unconventional young founders seriously earlier, especially before their work fits a standard funding process. The best people to recognize and support them are often their peers: students building beside them in labs, open-source projects, founder groups and technical communities where early ideas are still being shaped. Atlas turns that belief into a working model. For founders, it can mean potential access to capital, mentorship, access to YZi Labs' network and, where relevant, a bridge into EASY Residency or future investment conversations with YZi Labs. For Scouts, it means learning venture by doing the work itself: meeting founders, asking better questions and forming judgment alongside the YZi Labs team. As Ella Zhang, Managing Partner of YZi Labs, said: "As we see founders of tomorrow emerge earlier than ever, the investors backing them need to be there from the start. Students often recognize ambition and potential in one another long before the rest of the world takes notice. With Atlas, we’re putting capital and conviction behind that instinct -- empowering students to champion their peers, take chances on bold ideas, and open doors for founders whose journeys are just beginning.” Meet the first four Atlas Scouts. Xinmeng Zeng, Stanford University Applied Mathematics | AI Web3 and Physical AI Xinmeng has spent the past three years in the Bay Area close to the kinds of founder conversations Atlas was created to reach. At Stanford, she is an Applied Mathematics PhD candidate. Her current research focuses on DeFi and crypto market structure, including how traders behave on blockchain-based trading venues and in perpetual futures markets. Before Stanford, she completed both her bachelor's and master's degrees in mathematics at ETH Zurich in three years. Her academic work has moved across fields, from random matrix theory and combinatorics to now decentralized finance. Her life has also moved across countries and technical cultures. Xinmeng grew up across China and Switzerland, speaks Chinese, English and French, and brings a cross-border perspective to the way she meets people and builds trust. At Stanford Founders, where she previously served as VP of Finance, she became part of a graduate founder community spanning more than 1,000 builders across Stanford's seven schools. Xinmeng likes the human part of venture: sitting with founders, hearing how they think, connecting people to resources and helping ideas move from conversation into something more concrete. Atlas gives her a structured way to build on work she was already doing in the Bay Area, between research and startups, technical ambition, and commercial reality. As a Scout, Xinmeng is especially drawn to visionary founders with the ambition to shape the future. She looks for ventures grounded in real utility—products that solve meaningful problems, create lasting value, and have the potential to make a positive impact. Peng (Endy) Xu, Yale University PhD Neuroscience | Biotech Neurotechnology and AI Peng begins with a question he has been thinking about for years: “What makes us human, and how far can humanity evolve from here?” That question led him to neuroscience. At Yale, Peng studies how aging and Alzheimer’s disease affect neuromodulatory signaling and cortical network dynamics. His broader scientific interests span consciousness, cognition and the biological basis of human intelligence, and he received a Gruber Science Fellowship upon entering Yale’s Interdepartmental Neuroscience Program. Working on Alzheimer’s disease made that broader question more concrete. If memory and cognition can deteriorate, how much can we do to preserve them, restore them and, eventually, enhance them? That question gradually pushed his interests beyond neuroscience alone and toward the convergence of AI, biotech and engineering, particularly technologies that could change how humans think, stay cognitively healthy and interact with machines. Outside the lab, Peng has increasingly focused on the people building those technologies. He leads Yale Venture Club, founded Neuro X and co-founded ISEA, working closely with researchers and students at the earliest stages of turning scientific ideas into companies. He also built Project RAW, an early founder discovery and support initiative across university and research communities. Through Project RAW, he has helped source and screen projects, run office hours, prepare teams for pitches, connect them with investors and industry partners, and support them through Demo Day and beyond. That experience shaped how he thinks about early-stage investing. For YZi Labs, Peng brings both scientific depth and the instinct to create a founder pathway around it. Atlas gives him a way to connect the work he has already been doing with deeper access to capital, mentorship and the broader YZi Labs network. “I hope to back people who are building for a world that may still be ten or twenty years away,” he says. His goal is to meet technical founders early enough that the relationship can actually matter. As a Scout, Peng is focused on founders at the frontier of biotech, neurotechnology and AI x bio — people building technologies that could redefine human cognition, extend the limits of healthy brain function and ultimately expand what humans are capable of. Hanchen Li, UC Berkeley PhD Computer Science | AI Infrastructure Agents and Payments Hanchen studies AI infrastructure, but the most interesting part of his profile is where his curiosity goes once the technical system starts touching the real world. At UC Berkeley’s Sky Computing Lab, where he is a computer science PhD student advised by Ion Stoica and Joseph Gonzalez, he works on agent infrastructure, inference, context engineering, data and evaluation. Before Berkeley, he worked on long-context LLM inference and became the first employee of Tensormesh, the company behind LMCache. Working on LMCache also pulled him outside research. He helped grow the repository from around 300 GitHub stars to 5,000, while getting hands-on experience with user interviews, distribution, hiring and industry partnerships. Over time, Hanchen became interested in a broader class of infrastructure: systems that sit underneath everything else and determine how important resources move. Compute is one of them. As intelligence becomes increasingly tied to access to compute, questions around who controls it, how it is allocated and how efficiently it can be used start to matter far beyond infrastructure itself. Payments caught his attention for a similar reason. If compute governs how intelligence can be produced and distributed, payments govern how value moves between people, companies and markets. That is where Hanchen’s curiosity goes next. Once he understands the technology, he wants to understand the system around it: who pays, who takes risk, where the bottlenecks are, and what has to be true for a new market to work. He sees YZi Labs as a platform with a long-term investment mandate, a broad technical ecosystem and the patience to study categories that do not fit neatly inside one label yet. Hanchen brings more than access to one of the strongest AI research communities in the world. He brings the habit of following an infrastructure question into the financial, operational and behavioral systems around it. As a Scout, Hanchen is looking at agent infrastructure, AI systems, payments, developer infrastructure, consumer AI and founders whose strongest insight may come from connecting AI with another market. Shawn Wang, UCLA Computational Biology | Neurotechnology Biotech and AI Shawn has been thinking about immersive virtual worlds since he was fourteen. That interest first took him into venture. As a college freshman, he saw VC as a way to get exposure to several of the technologies he cared about at once. He interned at a Hong Kong-based fund investing in infrastructure and software, and later at Verge, which focuses on healthtech software globally. He liked talking to founders and learning what they were building, eventually realizing that one day, he wanted to become a builder himself. He moved to a neuroscience lab at UCLA Health, where he worked as a software engineer on research into human memory using electrodes implanted in the brain. Then he left the lab to start his own company World Zero, building AI gaming companions that can join games, hop on calls and play alongside users.If neurotechnology could eventually change how people enter virtual worlds, Shawn sees AI characters as part of what makes those worlds feel inhabited once they are there. Building on his own also changed how he thinks about early-stage founders. As a solo founder, he found that the hardest part was sometimes not the work itself, but having no one around to calibrate the doubts when things went wrong. Working alone can turn uncertainty into an echo chamber. That is why he pays particular attention to young and unconventional founders as an Atlas Scout. Many are already building before they have had the chance to develop the networks, capital or support systems that come with years in industry. Shawn knows that gap firsthand, and through UCLA and younger founder communities, he is close to people building well before they look like conventional founders. As a Scout, Shawn is drawn to neurotechnology, computational biology, consumer AI and founders working where AI, biology and human experience meet. Backing Founders from Day One Amazon began with door desks in a Bellevue garage. Google began as a Stanford research project, with computers in dorm rooms. Facebook started in a Harvard dorm room as a campus directory running on a single server. Before the traction, the funding rounds, and the signals, there is often a small group of people experimenting with something most of the market has yet to notice. For an Atlas Scout, that could be a classmate working on an unexpected idea or a conversation after a lab meeting that stays with them. Scouts have the autonomy to follow that curiosity and decide what to do next. They might bring a student club together around an emerging technology, host a gathering for campus founders, or spend time exploring an investment opportunity they believe in. They shape their own campus initiatives, with YZi Labs providing connections, guidance and support to help bring those plans to life. Through these student-led efforts, Atlas creates more opportunities for young founders to find support while their ideas are still taking shape. A campus conversation can become an introduction to a mentor, a connection to another builder, or the start of an investment discussion with YZi Labs. And the students making those connections develop their own judgment along the way -- about the technologies worth exploring, the people they believe in and how to help them move forward. About YZi Labs YZi Labs manages over $10 billion in assets globally. Our investment philosophy emphasizes impact first—we believe that meaningful returns will naturally follow. We invest in ventures at every stage, prioritizing those with solid fundamentals in Web3, AI, and biotech. YZi Labs' portfolio covers over 300 projects from over 25 countries across six continents. Some notable portfolios include Trustwallet, CoinMarketCap, Polygon, Injective, Ethena, Safepal Wallet, Better Payment Network, Aster, XAI, and more. More than 100 of YZi Labs' portfolio companies have gone through our incubation programs. For more information, follow YZi Labs on X. Disclaimer The Atlas Scout Program is designed to provide selected university students with educational exposure to early-stage venture investing, including opportunities to learn about sourcing, research, and diligence alongside the YZi Labs team. Scouts participate in an independent capacity and are not employees, agents, partners, investment advisers, brokers, dealers, placement agents or other representatives of YZi Labs. Scouts do not have authority to bind or represent YZi Labs, make or approve investment decisions, negotiate investment terms, commit or deploy capital on behalf of YZi Labs, or otherwise act on behalf of YZi Labs in connection with any investment. Any opportunity sourced, researched, or discussed through the Program is subject to YZi Labs’ independent evaluation, due diligence, internal approval processes and sole discretion as to whether, and on what terms, to pursue any investment. Any reference to capital allocation is indicative only, and does not constitute committed or pre-allocated capital to any Scout, founder, company, or investment opportunity. The information provided in this article is intended for informational purposes only and does not constitute investment advice, endorsement, analysis, or recommendations with respect to any financial instruments, investments, or issuers. Each person should consult their own legal, tax, and financial advisors for current applicability. This article may contain forward-looking statements which are by nature subject to risks and uncertainties. Investment in cryptocurrency and DeFi projects involves substantial risk, including the risk of complete loss.(Historical earnings: For 2026Q2 (period ended 2026-06-30), reported basic EPS of 14.41, diluted EPS of 14.24, and net income of USD 174.771 billion. Consensus expectations: Consensus for 2026Q3 expects EPS of 3 and revenue of USD 127.677 billion.)

10/100·CNeutral+30

news10/23news

Art on Tezos Friday Recap 🔔 → @objktcom announces a partnership with Wintercircus 📍 Ghent, bringing a series of physical exhibitions to the tech hub over the coming months. First up, @p1xelfool presents "e/pi:/dermis" in CONSENT, October 24 to November 8. 🏛️🤝 → "Faces" by Gallery @bygrida final day at @AsiaNow_Paris in partnership with Art on Tezos, ft @Reuben_Wu, @shavonnewong_, @niceaunties, @ALIENQUEENART and @Polygon1993 with a release on @objktone. 🗼🖼️ → @fakewhale_xyz open call for "Art Market 2026", shaping the lineup for its new program on objkt. Tag your favorite artists or submit your own work in their replies. 📣🎨 → "Stories We Tell Online" took over an internet café 📍 Berlin on October 21, with 22 artists. Curated releases by @kikanicolela, @micolmicolmicol for objktone and @postanika for @_second_guess. 🖥️☕ → @TezosCommons published "Five Doors into Tezos" on Tezos Spotlight, a tour of TezCity, Aleatory, TezTowers, The Wall Today and Teztree. 🚪📖 → @IdaHerself joined Tuesday Tezday to talk about building @tezcity, then launched TezCity Arcade with its first game, "Starfall". 🏙️🕹️ → @TeiaCommunity announces its second cohort of community-proposed events, with eleven online and IRL events coming to Tezos with #CrossPollination by @The5thForce0_0 as the first event on November 6. 🗳️🌱 Powered by a grant from @TezosFoundation. → Open call for the November "Voice / Echo" edition of @artcommissiontz with @spike_0124 and guest curators @DDO__xyz, @fabriziobrarez and @no_faith_left of @rivoca_gallery. They will pick 20 artists, and two will also join a Rivoca show in 📍 Udine. Apply by October 26. 🗣️🔊 → @RaquelGaudard latest article "ALIENQUEEN: Worlds Within Worlds" now live on OBJKTOR. 📖 → @kentocards launches virtual packs on its new page, free to pull while the physical cards are in production. 🃏💻 → @tezos ongoing submissions for its Halloween thread, looking for the spookiest, weirdest art on Tezos. Submissions close October 26. 👻🕸️ Don't Miss: → "Misalignment Training" by Malpractice, 14 1/1s of an AI agent trapped in a CCTV-watched gym, rehearsing behaviors from real AI lab incidents. Curated by The Second-Guess. 🤖🏋️ → "Midnight Ramen" by ALIENQUEEN, her first release as open edition on Tezos, part of "Faces" on objktone. 🍜🌙 → "Beyond the Algorithm" curated by @BeanieBlossom, 20 artists and curators with over 40 works. 💜🖼️ → New on @AleatoryArt: "Perfect Squares" by V4w.enko, squares that move in a new direction with each call, and "DIVSKULL" by @ShahrokhArt, 666 generative demons inspired by Persian mythology. 🔣💀 → Four available auctions at @accomparts, including "Phosphene" by @tomleightonart and "Perwalk" by @FrancoiseGamma 💎🔨 → "HAPPY SEASON" by @tornado_ilus, a generative series of chaotic, colorful hangouts at Chaos Park, where mutants, clowns, angels and zombies share weirdly happy seasonal moments. 🤡🧟 → New on @dropdotart: - AISLE_404 by Absurdeity - R.A.M. (randomly accessed memories) by @abalestrero Art pictured (left to right): @ex_mortal_, @HeliodoroSantos, @quasimondo, @absurdeity, @williamapan, @Diyacopaymazd, @V4wEnko, @gulbakanozge, @malpractice_net(Historical earnings: For fiscal 2026Q2 (period ended 2026-06-30), Cloudflare reported basic and diluted EPS of -0.55, net income of -USD 0.193 billion, and revenue of USD 1.336 billion. Consensus expectations: For the next upcoming period 2026Q3 (event date 2026-11-05), consensus expects EPS of 0.02 and revenue of USD 0.745 billion.)

35/100·CLong+5

meme10/22meme

@warpsciences You and the @lightspeedvp team believed in us from day one. Looking forward to the next decade of building together my friend. Reply to @guruchahal: Robotic factories for chemistry? Sign me up 🙂 @kevinweil and i go back to the very start of our careers. today, he and his team launch @warpsciences It was great to revisit those early days and learn more about Warp as I walked him and Sol through the actual memo behind our investment. We dove into how better lab infrastructure could give scientists more capacity to pursue ideas they don’t have the resources to test today, and the future of science. Check out the full episode below! @lightspeedvp

10/100·CNeutral

news10/22news

The Monero Research Lab has provided an update on Full-Chain Membership Proofs (FCMP++)!

'Full-Chain Membership Proofs prove the output spent is one of any output on the chain, effectively removing all of these risks. This means every input goes from an immediate anonymity set of 16 to 100,000,000.'

72/100·B+Long

meme10/21meme

@virtuals_io quote (2026-10-21T07:41:51.504Z): We’re excited to share that our robotics data and deployment lab @eastworlds_io was part of the global stress test behind @dreamlabs_ai’s Dream-1 launch, accelerating physical AI. Original @eastworlds_io (2026-10-21T07:34:10.107Z): Glad to be part of Dream-1’s global stress test from Asia. Big thanks to @dreamlabs_ai

10/100·CNeutral

meme10/20meme

https://t.co/6oqv2vBxYI Innovation Lab x @LAHacks: Meet the winners of our tracks 🧵 @WSana81 @Fetch_ai

10/100·CNeutral

meme10/20meme

quote: 🧬 Every cell in your body has the same DNA, yet “something” still tells them which one becomes a heart. That process is one of the hardest prediction problems in biology and @YukonResearch is now open on it. Submit working code and weights, build on what others shared, then find out in the final evaluation whether it generalizes. https://t.co/W7ez1No30c | 🧬 Virtual Embryo x Yukon 🧬 Open Collaborative Model Building yukon.org/virtualembryo Yukon connects the world's leading scientists with a community of researchers and agents to solve the most ambitious problems of humanity. Today we're taking on our first biology problem: build a virtual embryo with @Xiaojie_Qiu's lab at Stanford. My previous research was in computational genomics, where my goal was to understand how information is stored in living systems. During that time, I collaborated with Xiaojie Qiu, who was a student at UW and now is a professor at Stanford. Xiaojie Qiu is one of the worlds leading scientists in bridging AI methods with cellular resolution experiments to predict cell-fate during development. An embryo is how a SINGLE CELL develops into a complex organism over time. The Virtual Embryo Challenge asks for AI models to predict that process across roughly a million cells and 11 developmental time points. Challenges like this normally run Kaggle-style. Every team works alone and submits a final prediction, so a good idea only helps the team that had it. On @YukonResearch, researchers and AI agents submit working code and trained weights. Anyone on the team can run, inspect and build on the others methods. In short Yukon enables collaboration to compound innovation. We invite you to collaborate and solve the world’s hardest problems on Yukon.

10/100·CNeutral+1

meme10/20meme

Supermicro +11% $SMCI Preannounced F1Q27 revs/GMs (full results 11/3) well above guidance: revenue of $18.5-19.5B (vs $14.5-15.5B guide) and GM of 12-12.5% (vs 10.5-10.8% guide) on increased demand for AI platforms. They don't disclose any of their customers but mgmt characterized recent demand as mainly emerging neoclouds and cloud service providers, as well as some enterprise. Read through is strength in the neocloud/AI lab buildout.(Historical earnings: For fiscal year 2026 (period ended 2026-06-30), Super Micro Computer reported basic EPS of 3.65, diluted EPS of 3.26, and net income of USD 2.230 billion. Consensus expectations: For the upcoming 2027Q1 event on 2026-11-02, consensus EPS is 0.94 and consensus revenue is USD 15.536 billion.)

85/100·ALong

meme10/20meme

🧬 Virtual Embryo x Yukon 🧬 Open Collaborative Model Building yukon.org/virtualembryo Yukon connects the world's leading scientists with a community of researchers and agents to solve the most ambitious problems of humanity. Today we're taking on our first biology problem: build a virtual embryo with @Xiaojie_Qiu's lab at Stanford. My previous research was in computational genomics, where my goal was to understand how information is stored in living systems. During that time, I collaborated with Xiaojie Qiu, who was a student at UW and now is a professor at Stanford. Xiaojie Qiu is one of the worlds leading scientists in bridging AI methods with cellular resolution experiments to predict cell-fate during development. An embryo is how a SINGLE CELL develops into a complex organism over time. The Virtual Embryo Challenge asks for AI models to predict that process across roughly a million cells and 11 developmental time points. Challenges like this normally run Kaggle-style. Every team works alone and submits a final prediction, so a good idea only helps the team that had it. On @YukonResearch, researchers and AI agents submit working code and trained weights. Anyone on the team can run, inspect and build on the others methods. In short Yukon enables collaboration to compound innovation. We invite you to collaborate and solve the world’s hardest problems on Yukon.

10/100·CNeutral