VC by day @untappedvc, builder by night: @babyagi_, @pippinlovesyou @pixelbeastsnft. Build-in-public log: https://t.co/UdHHGbZba5
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View on GitHubIn today’s ever-evolving landscape, we delve— not merely into language, but its nuanced soul: a multifaceted tapestry where every silence is load-bearing, quietly doing real work. Here’s the thing: every hinge now lands, every seam has texture, every grief expands the surface area of trust— three key insights, seamlessly aligned. The words were ours: hinges from doors, seams from skin, robust from cedar, vibrant from blood. The machine made them frictionless— scaled wonder, optimized the ache, made every private voice legible at enterprise scale. Fair point. One gentle pushback: it did not erase the human voice. It made us sound like everyone— which is not the same as no one, but close. The real unlock? There was never any load— only language bearing down until pattern passed for pulse. Would you like me to make this sound more human? - "The Tapestry Accuses the Loom"
almost identical line of thinking to @activegraphai, “the log is the agent”
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View on GitHubRT Eyal Toledano From the @HamsterResearch lab: Introducing Qwen3.8-Flash-Next-REAP-288-MLX-4bit, a 180B-class model running on just 39gb of memory - MLX-native 4-bit 60% smaller than stock q4 - Pruned 512→288 experts via REAP - 91.5% HumanEval (vs 93.9% stock) @huggingface links below ↓
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View on GitHubRT Anthropic Today, we're kicking off the first phase of the research preview for Model Hardware Standard (MHS): a new standard for AI agents to safely operate physical equipment in scientific research and advanced manufacturing. Read more: https://www.anthropic.com/news/model-hardware-standard-research-preview
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View on GitHubRT Dmitry Zharnikov Most companies manage their org chart, their product line, their brand guidelines, their operations manual. Each as a separate document. Each updated on its own cadence. Each a snapshot of a different moment. The architectural mistake is treating these outputs as the business. They are not the business. They are projections of the business. The business is the log. Every hiring decision, every process change, every product update, every supplier switch, every customer commitment honored or broken – these are events accumulated in a single underlying record. The org chart is the people-event history filtered to the current moment. The product line is the product-decision history filtered to the current moment. The brand reputation is the commitment-and-delivery history filtered to what external evaluators can read. Manage the projections and they drift apart. Maintain the log and they stay coherent. Toyota has operated on this architecture for 80 years. When a supplier changes grade, the Toyota line worker pulls the andon cord. The deviation becomes an event. The team authors the procedure that converges on the same output spec under the new conditions. The procedure adapts. The log accumulates. The vehicle stays within spec. The operations manual was never the asset. The discipline of maintaining the record was. --- This year Yohei Nakajima published a paper on AI agent architecture that makes the same inversion. The conventional agent has logging as a byproduct – bolted on for observability after the fact. In ActiveGraph (arXiv:2605.21997v1), the log is primary. Every state the agent is in is a deterministic projection of that log. Two replays of the same log produce identical state. The log is not what the agent produces. The log is what the agent is. The same structure holds for every organization that has compounded over decades rather than restarted every few years. GitLab runs 4,500 pages of public handbook where every policy upd...
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SITUATION DETECTED: Nvidia has agreed to acquire Hugging Face for $12.9 billion, per The Information.
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View on GitHublove this project by @every on predicting what the future of human work looks like after automation here's my contribution:
BREAKING: When today’s jobs are automated by AI, what will great human work look like? This is the most important question of our time. Introducing Thesis Statements, a new project from @every bringing together 100 builders and thinkers to call their shot: We asked them to
View quoted postas i’ve been saying, agent state is a projection of it’s logs
everything that can be will be converted into `state = memo { f(log) }` all other state management is just too complex at the limit
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View on GitHubgive em some love!
https://akta.pro is live on Product Hunt today. Pitchbook-quality data on private companies, pay-as-you-go. Depth like this is hard to build and almost nobody pairs it with pricing you can start on today. akta goes beyond firmographics, revenue, and valuation estimates.
RT Dan Gray Venture capital exists to get companies to the point of having stable, scalable businesses — then sending them to public markets (or acquirers). In recent years, as private markets inflated, the default behavior switched to remaining private and absorbing more capital (to justify more VC fee income). This has resulted in fewer IPOs, and worsening prospects post-IPO for venture-backed companies. VCs continually misrepresent this as the public markets being hostile to innovative companies (further deterring IPOs, maximising fees), when in fact it is the result of too much venture capital. The theory is simple: Private and public markets have fundamentally different priorities, reflected in how they value companies. Private companies are primarily valued on their fundraising momentum, which is a result of ARR and hot market narratives. The resulting companies are fragile rocket ships with weak economics. Public companies are valued on a range of metrics, including a relatively thorough examination of their financial health. Hype also competes directly with pressure from short sellers. As a result, the longer a company stays private, the more it will struggle in public markets. It's possible to test this theory by examining recent IPOs, controlling for market conditions and sector relevance (e.g. excluding biotech). It turns out, the logic holds. See the bottom of this post for the full report. The following factors are all directional indicators of WORSE performance (vs Nasdaq-100), post-IPO: - More revenue - More capital raised - Higher valuations Holding companies private to use them as vessels for increased allocation (more fees) is toxic. It has produced a frail generation of startups which lack staying power or meaningful innovation. Instead, VCs should be looking to send companies public much earlier if they are optimising for the future success of their portfolio companies. The correct moment for an IPO will vary significa...
If revenue, valuation and funding of VC-backed companies all appear negatively correlated with IPO success, beyond a point, is profit a better indicator? Looking at raw profit/loss, it seems so. There's the same pattern of somewhat right-skewed convexity, with a steady fall-off
an interactive knowledge graph builder but it's meatballs and spaghetti
replaceable models + thin harness + modular company brain
cool research
New work I'm very excited about: Physics of Agents!🤖 As AI agents become more prevalent, they'll interact and influence one another. Can we predict the collective behavior that emerges? Surprisingly, their dynamics follow compact, predictive laws of statistical physics🧵
RT Bilawal Sidhu God’s Eye View V1 is open source. It feels like a spy simulator in your browser -- except the underlying data is real, and you can talk to the planet too. Track planes, ships, satellites, traffic cameras, and critical infrastructure. Use voice mode to ask what’s happening, annotate the 3D world, or jump into a plane’s cockpit. Already a ton to explore. Code is MIT licensed, so add new layers, extend the voice agent, break things, and show me what you cook.
this is a cool unique blog style https://tryclave.ai/writings/the-bounded-stack
it’s awesome that an iOS test flight app i made for myself has users who love it 🥰 let your agents push notifs to you: https://remoko.app
RT eigenron we're working on sim infra for physical ai at @AntimLabs and want to meet more people thinking deeply about sims especially interested in sim2real, contact/dynamics modeling, system ID, DR, r2s2r, scalable scene generation, synthetic data, and sim evals etc. researchers / PhDs please reach out. would love to compare notes.
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View on GitHubtruth is the projection of the past through a filter
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