Problem solver, learner, developer, /[net|sys]admin/; from Cuba.

Ottawa, ON, Canada
Joined August 2009
Camilo retweeted
We have completed breakover operations for the Neutron Stage 2 tank assembly, rotating the stage horizontal – a critical step in the handling of large rocket sections for integration and assembly. Here’s a last look at Stage 2 on the Neutron Factory floor before it’s wrapped up (literally) for barge shipment to LC-3 on Wallops Island where its fluid systems will be tested and its Archimedes vacuum engine installed.
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Camilo retweeted
We use Grok Bot to spot incidents in our support queue and quickly respond to every associated ticket. In one incident, it cleared 204 tickets in about 10 minutes, with one engineer approving the batch.
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In our new benchmark AA-PersonalityBench, GPT-4o, Llama 4 Maverick, and GPT-3.5 Turbo, the three oldest models measured, rank highest on the Sycophantic personality trait. Grok 4.7, Claude Fable 5.1, and Inkling rank lowest ➤ @AIatMeta models are highly concentrated near the top: all five Meta models measured rank 65 or higher (Llama 4 Maverick 97, Muse Spark 1.3 87, Muse Glimmer 79, Muse Spark Open 76, Muse Wonder 65) ➤ @GoogleDeepMind models are spread out along the Sycophantic range: Gemini 3.1 Pro Preview ranks 89, Gemini 4 Argon 81, and Gemini 3.8 Flash 28, ranking from the top quartile to almost bottom quartile ➤ @AnthropicAI models skew on the lower end of the Sycophantic range: every Claude model measured ranks 55 or below (Claude Haiku 5.5 55, Claude Opus 5.5 46, Claude Sonnet 5.5 30 at medium effort and 25 at max, Claude Fable 5.1 4) ➤ @SpaceXSI's Grok 4.7 model ranks the lowest of all models measured. Congratulations @elonmusk!
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Camilo retweeted
Cloudflare has deployed default web application firewall (WAF) protections for newly disclosed PHP vulnerabilities before public disclosure. The rules use request and response signals to stop exploit attempts and prevent exposed data from reaching attackers. cfl.re/488w8dc
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Camilo retweeted
Grok Bot is now one step closer. Set it as your iPhone's Action Button and press it to talk with Bot.
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Once Intelligence Index thresholds are reached, the cost of accessing that level of intelligence reduces fast. Reaching 30 on the Intelligence Index now costs 86x less per task than when first reached Existing intelligence thresholds have become cheaper to reach, while the highest-scoring model costs more than the highest-scoring from one year ago. Key takeaways: ➤ Reaching 20 is 123x cheaper than ~13 months ago; reaching 40 is 33x cheaper than ~5 months ago: measured models first reached these thresholds in September 2025 and May 2026. ➤ GPT-6 Luna (high) reaches 30 for $0.03/task: @OpenAI's model is 86x cheaper per task than @AnthropicAI's Claude Sonnet 4.6 (Adaptive Reasoning, Max Effort), which first reached 30 in February 2026 at $2.49/task. ➤ Claude Haiku 5.5 (xhigh) is now cheapest to reach 40: it scores 41 at $0.12/task, 5% below GPT-6.1 Sol (low). ➤ Reaching 50 is 18x cheaper than when first reached: GPT-6.1 Sol (high) reaches it for $0.32/task. ➤ The highest measured score has risen from 21 to 58 in a year, at ~11x the cost: Claude Opus 5.5 (Adaptive Reasoning, Max Effort, Default Fallback) costs $5.98/task. As of October 20, 2026, using measured v4.3.2 results and current prices, including for historical models.
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This illustrates the point I’ve been making about the limits of centralized approaches to SI safety in cyber. OpenCode (and earlier Hugging Face) hit the same wall mid-attack: frontier models refused to analyze the very exploits needed for defense because the payloads tripped safety filters. The guardrails backfired. Meanwhile, the attackers found a way around restrictions to access advanced capabilities. This is not surprising. Chinese models are only about 6–9 months behind the American frontier in cyber. Obviously the U.S. has no jurisdiction over them. The only durable response is decentralized: make powerful models available so defenders can build and run their own cyber defenses. The only solution to SI-powered cyberattacks is SI-powered cyber defense.
OpenCode is currently under a sustained cyberattack, and mid-incident they ran into the same problem Hugging Face did: the frontier models they were using for defense began refusing to help fight attacking agents because analyzing the attacks started triggering safety guardrails.
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Replying to @GergelyOrosz
I am from 🇫🇮 and Linus is never sugercoating
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Camilo retweeted
Turns out the future does have flying cars
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Bernie Sanders says the top 1% owns more than the bottom 93%, that fewer than a thousand billionaires got $2.2 trillion richer last year, and that it's "obscene." It's the most seductive and most wrong economic argument of our time. Let me explain why. First, wealth distribution follows a power law. Always. Everywhere. Books, music, startups, followers on X, goals in soccer. A small minority captures most of the value. That's not a bug of capitalism. It's the mathematical signature of every system where value gets created. So the only question that matters isn't "how big is the rich's slice?" It's "is the cake growing, and is the slice of the poorest growing with it?" And the answer is yes. In 1990, more than one human in three lived in extreme poverty. Today it's about one in ten. During exactly the period when billionaires multiplied. Bernie shows you the slice. He never shows you the cake. Second thing he won't tell you: past a certain level, wealth stops being consumption. It becomes capital allocation. Elon Musk isn't sleeping on a pile of cash. He owns stakes in Tesla, SpaceX, xAI. Jeff Bezos owns Amazon stock. That "$2.2 trillion" isn't sitting in a checking account. It's factories, rockets, data centers, millions of jobs. Nobody can eat $100 billion. You can only decide where to invest it. Once you understand that, the whole debate changes. The real question becomes: who allocates capital better? The people who built Amazon, SpaceX and Nvidia? Or politicians? A 5% wealth tax isn't "taking money from the rich." It's taking investment decisions away from people who proved they can create value and handing them to people who proved the opposite. Because the fundamental difference between an entrepreneur and a politician is consequences. The entrepreneur invests his own money. If he allocates badly, he loses everything. The market corrects him brutally, no appeal. That's why most startups die: the system kills bad decisions. The politician invests other people's money. If he allocates badly, nothing happens. Worse, he gets a bigger budget to "fix the problem." Milton Friedman put it better than anyone. There are four ways to spend money. Your money on yourself: you care about price and quality. Your money on others: you care about price. Others' money on yourself: you care about quality. Others' money on others: you care about nothing. Government is the fourth box. By design. Perfect example: California high-speed rail. Approved in 2008 for about $33 billion. Current estimated cost: over $100 billion. Passengers carried: zero. No entrepreneur would have survived that. The politicians who pushed it built careers on it. And when allocation has no consequences, it eventually finds a buyer. A politician who controls billions without accountability becomes the most profitable target in the world for anyone who wants to steer that money. The irony is that the left that rails against billionaires is itself funded by billionaires. George Soros is one of the biggest Democratic donors in history. The Gates Foundation shapes public health policy across the planet. Politicians don't fight billionaires. They pick their own. The ones who fund the state over the ones who compete with it. So if we actually want fewer poor people, we have to stop judging ideas by their intentions and start judging them by their results. And the results are brutally clear. China, 1978: Deng Xiaoping opens the economy to markets. More than 800 million people escape extreme poverty. The largest retreat of misery in human history. Not through redistribution. Through the freedom to build. India, 1991: liberalization. Same movie. South Korea and North Korea: same people, same language, same starting point in 1953. One became one of the most advanced economies on earth. The other has famines. Poland and Ukraine: comparable living standards in 1990. Today the average Pole is more than three times richer than the average Ukrainian. Argentina: a year and a half of liberalization, and the poverty rate falls from over 50% to around 30%. No country in history escaped poverty by punishing the people who build. Every single one did it by letting them build. And if you want to see what Bernie's program looks like in real life, you don't have to imagine it. It exists. It's called France. We've been running it for 45 years. Mass nationalizations in 1981. Two years later, Socialist president Mitterrand has to reverse course into austerity. Retirement at 60. The 35-hour workweek. A wealth tax for 35 years. Hundreds of wealthy households left every year for Belgium, Switzerland, London, taking their capital, their companies and their future taxes with them. Macron finally scrapped it in 2018. Hollande's 75% tax: raised a few hundred million, drove talent out, abandoned after two years. One of the highest tax burdens in the OECD. Public spending around 57% of GDP, a record in the developed world. Last balanced budget: 1974. Public debt: over €3.4 trillion. Mass unemployment for four decades. If taxing the rich and growing the state made people prosperous, France would be the richest country on the planet. It isn't. GDP per capita in France is barely more than half of America's. It's lower than Mississippi, the poorest state in the US. Not a single global tech giant. Our best engineers build Silicon Valley instead. I've been going back and forth between Paris and San Francisco for years. I see it every week. And California is about to replay the movie. Prop 40, on the ballot November 3rd, would take 5% of billionaires' net worth. Even Gavin Newsom, a Democratic governor, opposes it. The state's own nonpartisan budget analyst warns that income tax revenue could drop every year if the wealthy leave. Larry Page, Sergey Brin and Peter Thiel have reportedly already started moving their assets out. You don't fight poverty by shrinking the top. You fight it by growing the cake. Bernie wants a society where nobody has too much. I want a society where nobody has too little. The first has been tried everywhere and produces equality in stagnation. The second lifted a billion people out of misery. Choose.
The top 1% owns more wealth than the bottom 93%. 1 man owns more wealth than the bottom 53% of households. Less than a thousand billionaires got $2.2 trillion richer in the last year. Obscene. Yes. We need a 5% billionaire wealth tax in California and throughout America.
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Nvidia’s Nemotron 3.5 Super VL is now the leading US open weight model, scoring 26 on the Artificial Analysis Intelligence Index Nemotron 3.5 Super VL achieves twice the intelligence of its predecessor, Nemotron 3 Super (13), and does so using ~60% fewer output tokens per task It launches alongside Nemotron 3.5 Bolt 74B-A9B 24GB, the first model in its new Bolt family, which scores 21 on the Intelligence Index Congratulations to @NVIDIAAI on the releases! Key Takeaways: ➤ Leading US open weight model: Nemotron 3.5 Super VL scores 26.5, edging out Thinking Machines' Inkling Small (25.7) and ahead of NVIDIA's Nemotron 3 Ultra (23) and Meta's Muse Glimmer (17) ➤ Bolt comes within 2 points of Ultra: Nemotron 3.5 Bolt 74B-A9B 24GB scores 21, 1.5 points behind Nemotron 3 Ultra 550B A55B (23). The 2 bit memory has about a seventh of Ultra's parameters (74B vs 550B) and a sixth of its active parameters (9B vs 55B) ➤ Super 3.5 VL near lossless in NVFP4: Nemotron 3.5 Super VL releases in NVFP4, scoring within 0.1 points of its BF16 weights on the Intelligence Index, with no component moving by more than 2.6 points Nemotron 3.5 Super VL details Context window: 1M tokens Modalities: Vision and text input; text output Parameters: 120B / 12B Nemotron 3.5 Bolt 74B-A9B 24GB details Context window: 256k tokens Modalities: Vision and text input; text output Parameters: 74B / 9B
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Camilo retweeted
🚀 Zed v1.24 is out! You can now create Git tags directly in Zed. Use `git: create tag at head` from the command palette, or choose `Create Tag…` from a commit's context menu in Git history or Git Graph. Thanks cppcoffee!
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SpaceXAI’s Grok Voice 3.0 is the new leading Speech to Speech model, debuting at #1 on the Artificial Analysis Speech to Speech Index at 86.9, while also being competitive on latency Grok Voice 3.0 is @SpaceXSI 's successor to Grok Voice 2.0, a Speech to Speech model available through the SpaceXAI Realtime API at $0.08 per minute. We evaluated Grok Voice 3.0 with the Rex voice through the SpaceXAI Realtime API. Key takeaways: ➤ Speech to Speech Index: Grok Voice 3.0 debuts at #1 at 86.9, ahead of GPT-Live-1 (Astra, medium) at 83.2, Gemini 3.8 Live Extended Thinking (High) at 82.6 and GPT-Live-1 (Sol, low) at 80.1. It is up on Grok Voice 2.0 at 81.3 (+5.6 points) and Grok Voice 1.0 at 73.7 (+13.2 points), released just under six months ago. The Index averages Speech Reasoning (Big Bench Audio), Agentic Performance (Tau Voice), Arena Preference, and Task Success Rate ➤ Speech Agent Arena: Grok Voice 3.0 ranks #3 in preference at Elo 1070, behind Gemini 3.1 Flash Live Minimal (1100) and Gemini 3.8 Live (1088) and ahead of GPT-Live-1 (Sol, low) at 1057, and #1 on Task Success Rate at 94.8%, highest on the board, just ahead of Grok Voice 2.0 at 94.6%. Grok Voice 2.0 trails at Elo 1011 ➤ Tau Voice: Grok Voice 3.0 takes the #2 spot on our Tau Voice benchmark implementation at 71.6%, behind GPT-Live-1 (Astra, medium) at 74.5% and ahead of Gemini 3.8 Live Extended Thinking (High) at 68.6% and GPT-Live-1 (Sol, low) at 59.3% - up from 56.5% for Grok Voice 2.0 ➤ Big Bench Audio: Grok Voice 3.0 scores 98.5% on audio reasoning, ahead of Gemini 3.8 Live Extended Thinking (High) at 97.7% and Grok Voice 2.0 at 97.2% ➤ Speed: Average Time to First Audio on Big Bench Audio is 0.81 seconds for Grok Voice 3.0, well ahead of GPT-Live-1 (Sol, low) at 1.24s, GPT-Live-1 (Astra, medium) at 1.34s and Gemini 3.8 Live Extended Thinking (High) at 1.35s, though slower than Grok Voice 2.0 at 0.70s ➤ Cost: Grok Voice 3.0 costs $4.80 per hour of input audio, the same as Grok Voice 2.0. That is above GPT-Live-1 (Sol, low) at $4.47 and Gemini 3.8 Live Extended Thinking (High) at $3.50, cheaper than GPT-Live-1 (Astra, medium) at $5.83, and ~2.2x cheaper than GPT-Realtime-2.1 High at $10.75 Congrats to @elonmusk and the @SpaceXSI team 🚀 See below for more detail ⬇️
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Camilo retweeted
🚀 Introducing MiniCPM-V 4.7, our new open-source MLLM series! Advancing the Performance–Efficiency Pareto Frontier. It brings strong multimodal capabilities to iOS and Android devices with extreme efficiency. Two new models: 🔹 MiniCPM-V 4.7 35B-A3B — Bring SOTA performance to local devices with newly introduced LES (Lookahead Expert Scheduling) technique, a new milestone of on-device multimodal AI. 🔹 MiniCPM-V 4.7 1B — Lightweight, efficient multimodal AI. Easier to deploy. ⚡ What's new? SOTA performance: Competitive results across 34 benchmarks spanning multimodal understanding, STEM reasoning, OCR and long-video comprehension. Fast on-device inference: LES predicts and preloads expert weights to reduce inference stalls, boosting 5× speedup on iPad Pro M4 (16GB) with byte-for-byte identical outputs. It enables MiniCPM-V 4.7 35B-A3B to achieve 17+ tokens/s on iPad Pro M4 (16GB) and 13+ tokens/s on iPhone 17 Pro Max, while costing only 3GB memory 🤯 Efficient visual processing: 4× and 16× hybrid visual token compression. Even at 16× compression, 35B-A3B scores 90.4 on OCRBench, 5.2 points ahead of Qwen3.6 35B-A3B. Easier customization: We introduce Self-Replay Fine-Tuning, a simple way to customize new target capabilities at low cost while maintaining general performance. Broad hardware support: Day-0 adaptations for Apple, Intel, AMD, Arm and Rockchip, with many more platforms supported through FlagOS! Download, deploy, and build something we haven't imagined yet. 👀👇 🔗 GitHub: github.com/OpenBMB/MiniCPM-V 🤗 Hugging Face: huggingface.co/collections/o…
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grok @bot 0.70.2 is rolling out! - each bot can claim its own email address at @mail.grokbot.com and draft emails for you to send - apps like Figma, Notion and Canva show up as live cards right in the chat - bots can search X and read public posts and profiles without connecting an X account - describe what you want and your bot suggests a matching template - shared pages can be downloaded as a pdf - an approval check before anything irreversible and much more! x.ai/changelog/bot
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We have measured intelligence. Now it's time to see it. We are launching AA-3D, our new benchmark for how well AI models build interactive 3D scenes. Each model works as an agent in an offline sandbox and turns a written brief into a three.js web page. A human panel of judges compares pairs of scenes built from the same brief without knowing which model made which. AA-3D details: ➤ 55 written briefs across seven domains, including landmarks, machines, living bodies, games, and space. Each brief says what the scene must show and how people should interact with it, and leaves the rest to the model ➤ Each model gets up to three hours and 250 turns. Its sandbox has Blender, Rapier physics, Python, a headless browser to test its own work, and a CC0 library of materials, 3D models, and characters ➤ Panelists spend at least 30 seconds with each scene before they vote. One comparison in every four is a validation check ➤ Over 10,000 counted votes from over 1,000 panelists rank 21 models by Elo, with 95% confidence intervals Key findings: ➤ Four models are statistically tied at the top: Claude Sonnet 5.5 (1194), Claude Opus 5.5 (1190), GPT-6 Astra (1165), and Claude Fable 5.1 (1131). The 95% confidence intervals of the other three overlap Claude Sonnet 5.5's ➤ AA-3D Elo rises with intelligence: each point on the Artificial Analysis Intelligence Index is worth about 18 Elo (Pearson 0.92) ➤ The best-placed open weights models, Kimi K3 (982) and MiMo-V2.6-Pro (977), rank 11th and 12th, more than 200 points behind first place ➤ A scene costs $0.20 to $32.08, depending on the model. The cheapest, GPT-6 Luna, ranks eighth More results, more scenes, and how AA-3D works follow in the thread below.
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Camilo retweeted
Origin, Cursor’s code hosting platform, now supports over 20 integrations. Connect your repos to tools for CI, deployments, code review, security, monitoring, and project management.
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Gemini 4 Argon is now GA. Argon ranks equal to GPT-6 Astra on the Artificial Analysis Intelligence Index at 60% of the Cost per Task with discounted prices until Nov 30 Key takeaways: - Google is back to having a frontier model released to the public: This is Google's first proprietary model above the Flash class in over 7 months - Pricing temporarily discounted to 50% until November 30: Gemini 4 Argon has a Cost per Task of $1.99 with discounted prices, a ~40% reduction compared to GPT-6 Astra (max) for a comparable level of Intelligence. It is currently priced at $2/$10 per 1M input/output tokens with a 95% discount for cache reads (up from 90% from previous Gemini models). Prices will increase to $4/$20 after November 30 - Large improvements in agentic performance: Gemini 4 Argon shows substantial improvements in agentic evaluations such as AA-Briefcase, AutomationBench-AA, Terminal Bench 4. This is an area in which Google's models have historically underperformed compared to leading peers Lowest hallucination rate among leading models: On AA-Omniscience, Gemini 4 Argon has a 15% hallucination rate, the lowest of any model scoring 45+ on the Intelligence Index
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211BSD UNIX is 47 years old. For almost 50 years, the only way to get data off and onto a UNIX PDP-11, other than removable media, has been FTP. Until now. Now I've built SMB file sharing, the most exciting development to happen to a market of about seven people in a long time :-) I'm still pretty stoked that it works, though! And it handles Y2K dates... and passwords, permissions, etc. dir \\pdp-11\share
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Gemini 4 Argon is rolling out to Google AI Pro and Ultra subscribers globally starting today. Learn more about Gemini 4 Argon and additional updates coming to the Gemini app in our blog: goo.gle/4B9P74A
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