Mind Monster | AI & Robotics| Drones | Inventor | Founder | Making AI Training & Inference absurdly affordable for businesses @pandoradynamix

Mars
Joined December 2016
Mr V retweeted
With the way game bytecodes are being AI Funked (Reverse Engineered) the games that will stand the test of time, business wise are MMORPGS or social Games as a whole where you interact without another human (My opinion). This trend is about to get into bank apps but silently
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Mr V retweeted
Andrej Karpathy
@karpathyOct 11
Dusting off this tweet from April because this gap in shared understanding of LLM capability is *widening*. It's now less "two groups of people speaking past each other" and more a sharp funnel. - Napkin math somewhere around 6B people (~75% of the population) have barely come in contact with LLMs at all. - Around 1-2B (~20%) are casual and infrequent users of free-tier ChatGPT-like products. This group sees derpy chatbots and treats them a bit like a better Google search, a writing aid, or etc. Maybe an agent tries to book you a flight. I have non-tech friends who (reasonably, imo) say they have not much use for it at all. Even many professionals outside of math&code are in this tier. For example, execs and many other functions spend a lot of their time talking to other people, so while they understand what is happening intellectually, it is still second-hand and a bit abstract. - Now we get to professional use of frontier-grade LLMs in math&code. Somewhere around 20M people (0.2%) see first-hand that large, complex projects that used to take them weeks/months can now be completed by agents with a prompt. Building apps, copying apps, translating apps, decompiling apps from binaries... This has all happened very quickly and recently - less than 1 year ago, I was writing code manually by hand, typing memorized computer code commands into a code editor character by character, occasionally pressing Tab to autocomplete a little chunk of code. - And finally we get to the ~5,000 people (~0.00006%) with access to frontier-grade systems internally. The external world has seen the preview. It looks like swarms of thousands of agents collaborating over weeks on software mega projects: minting zero days, running cyber attacks and defenses at machine speeds, discovering new science, advancing the frontier of mathematics. Things that would have taken top professionals in the industry years of work. Meanwhile, human review and comprehension are starting to fall behind. For example, people are still involved in the "archeology" of the OpenAI-HF incident from many months ago. Mathematicians may be poring over the 722 manuscripts on frontier mathematics for a while. The funnel is driven by a combination of factors: 1. The impact scales with ambition, problem size, and horizon. A question with a paragraph answer barely stresses the system. You need a reservoir of big, difficult problems that you really care about. This aspect drives the consumer / professional dimension of the funnel. 2. The jaggedness of the system (which I have written about a lot separately). Capability peaks in domains that are digital, verifiable and economically valuable. This is because LLM capability emerges from reinforcement learning on verifiable rewards on a curated environment mixture driven by revenue potential. This aspect primarily drives the area (e.g. math&code) dimension of the funnel. 3. Access. Free-tier, paid-tier, internal. So this is the weirdness of the moment. The general public has mostly not interacted with these systems. When they have, it looks like a derpy chatbot. The majority of professionals still see only a modest uplift. And a small sliver of professionals are experiencing the vertigo of the curve going vertical. And it is all happening at the same time.
Andrej Karpathy
@karpathyApr 9
Judging by my tl there is a growing gap in understanding of AI capability. The first issue I think is around recency and tier of use. I think a lot of people tried the free tier of ChatGPT somewhere last year and allowed it to inform their views on AI a little too much. This is a group of reactions laughing at various quirks of the models, hallucinations, etc. Yes I also saw the viral videos of OpenAI's Advanced Voice mode fumbling simple queries like "should I drive or walk to the carwash". The thing is that these free and old/deprecated models don't reflect the capability in the latest round of state of the art agentic models of this year, especially OpenAI Codex and Claude Code. But that brings me to the second issue. Even if people paid $200/month to use the state of the art models, a lot of the capabilities are relatively "peaky" in highly technical areas. Typical queries around search, writing, advice, etc. are *not* the domain that has made the most noticeable and dramatic strides in capability. Partly, this is due to the technical details of reinforcement learning and its use of verifiable rewards. But partly, it's also because these use cases are not sufficiently prioritized by the companies in their hillclimbing because they don't lead to as much $$$ value. The goldmines are elsewhere, and the focus comes along. So that brings me to the second group of people, who *both* 1) pay for and use the state of the art frontier agentic models (OpenAI Codex / Claude Code) and 2) do so professionally in technical domains like programming, math and research. This group of people is subject to the highest amount of "AI Psychosis" because the recent improvements in these domains as of this year have been nothing short of staggering. When you hand a computer terminal to one of these models, you can now watch them melt programming problems that you'd normally expect to take days/weeks of work. It's this second group of people that assigns a much greater gravity to the capabilities, their slope, and various cyber-related repercussions. TLDR the people in these two groups are speaking past each other. It really is simultaneously the case that OpenAI's free and I think slightly orphaned (?) "Advanced Voice Mode" will fumble the dumbest questions in your Instagram's reels and *at the same time*, OpenAI's highest-tier and paid Codex model will go off for 1 hour to coherently restructure an entire code base, or find and exploit vulnerabilities in computer systems. This part really works and has made dramatic strides because 2 properties: 1) these domains offer explicit reward functions that are verifiable meaning they are easily amenable to reinforcement learning training (e.g. unit tests passed yes or no, in contrast to writing, which is much harder to explicitly judge), but also 2) they are a lot more valuable in b2b settings, meaning that the biggest fraction of the team is focused on improving them. So here we are.
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Mr V retweeted
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"Looped Diffusion Transformer" This new paper reuses the same Transformer blocks multiple times within each denoising step, repeatedly updating the hidden state to improve the prediction without increasing the model’s parameter count at inference-time. The found that a 260M model beats models up to 6.5x larger, and extra loops improve performance more than spending the same compute on extra denoising steps. alphaxiv.org/abs/2609.40305
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Open-source magnetic tactile sensor for $5! 🧲 Researchers from New York University introduced a magnetic tactile sensor that's low-cost, and easy to fabricate, democratizing tactile sensing for robotics. Operating in unstructured environments like homes and offices requires robots to sense forces during physical interaction. Yet the lack of a versatile, accessible tactile sensor has led to fragmented solutions and often force-unaware, sensorless approaches. Building an eFlesh sensor requires four components: a hobbyist 3D printer, off-the-shelf magnets (less than $5), a CAD model, and a magnetometer circuit board. The sensor is 3D printed with magnets embedded in the middle layer. Based on chosen mechanical properties, magnets displace in response to contact forces, measured by a magnetometer underneath. An open-source design tool converts simple OBJ/STL files into 3D-printable STLs. This enables application-specific sensors for robot hands, grippers, quadruped feet, and more. Slip detection generalizes to unseen objects with 95% accuracy. Visual-tactile control policies improve manipulation by 40% over vision-only baselines, achieving 90% success on precise tasks like plug insertion and credit card swiping. All design files, code, trained models, and conversion tools are openly available. 🔗 Project page: e-flesh.com ~~ ♻️ Join the weekly robotics newsletter, and never miss any news → ziegler.substack.com
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🚨 side project alert 🚨 Announcing Muse Gadgets, an open source ESP32 firmware and Linux sdk so that you can make hardware devices that work with Muse. Grab an API token from gadgets.muse.ai and point your favorite coding agent at the github repo to build your own peripherals for Muse.
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Mr V retweeted
Found a way to fly 5inch FPV drone with 2300KV motors and an overkill 5200mah battery, inside the house without crashing it, if you have tried messing around with one of this you could perceive how unstable they can be when you testing. Weighs almost 700mg crashing is a no no.
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Up to $5.5M to move your startup to Qatar. Just an MVP gets you in the door. The Startup Qatar Investment Program (backed by QDB) funds tech startups to launch or expand in Qatar. Two tracks: START: up to $1.1M if you have a proof of concept or MVP GROW: up to $5.5M if you're already established and expanding What else you get: - Entrepreneur visa + flexible work visa - Registration and license fees waived - Subsidized housing - Subsidized co-working space - Access to R&D and innovation grants - Mentoring, training + help hiring talent and interns - Your product showcased at exhibitions Sectors they want: - AI & ML, B2B SaaS, FinTech, HealthTech, Cybersecurity, Climate Tech, Robotics + more - Not on the list? It's open to any innovative startup Apply link below 👇 startupqatar.qa/en/investmen… Bookmark this + tag a founder looking for a new market.
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It will be much harder to change your world view after you get addicted to talking to an AI avatar. Choose carefully now or always be in the tribe you are in. And believing in a "soul" makes you easier to control when you do. Unpopular lessons from brain computing pioneer I talk with frequently.
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Mr V retweeted
Geoffrey Hinton
@geoffreyhintonOct 2
The idea of an intelligence explosion caused by recursive self improvement has been around for a long time but until very recently it did not seem imminent. Now many leading researchers think it may happen quite soon. You can read our paper about it here: casp.ac/reports/intelligence…
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Digital humans are finally arriving. This got a lot of hate. “Why do this?” Or worse. I wish it were pitched as the user interface of the future rather than something to stick in a video call. In a decade when you are talking to groups of these hope you remember how they were received initially.
The whole point of building Tavus has been simple: talking to a machine should feel as natural as talking to a friend or coworker. It’s hard to describe all the tiny nuances that make a conversation feel human. The little expressions. Moving around in your chair. Knowing when to speak and when to listen. The dance of it all. Griffin is by far the closest anyone has come to a model that can capture those nuances. The first time I saw it being used, I had no idea I was watching our model rather than just a normal video call. I’m so incredibly proud of this team and what they’ve built.
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Mr V retweeted
Introducing Griffin, the first model to pass the video Turing test. 48% of people who talked to it live thought it was a real human. Previous systems have had a pass rate <3%. It is #1 on NVIDIA's benchmark for full-duplex AI video. It’s the first Human Interaction Model (HIM).
Readers added context they thought people might want to know
The 48% figure and "video Turing test" claim are from Tavus's own study of 54 one-minute calls, not independently verified or using a standard protocol. Griffin-Lite leads NVIDIA's VideoFDB benchmark on their public leaderboard. cellcog.ai/blog/tavus-gri… research.nvidia.com/labs/amri/proj… tech-ish.com/2026/10/02/tav…
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Replying to @dylanmcguir3
@dylanmcguir3 and I just raised a $7.5M pre-seed led by @a16z to build a robotic surgeon @alephsurgery Much of the early investment in Physical AI has focused on industries where labor is relatively abundant and low-cost. We believe the biggest opportunities to change the world lie at the opposite end of the spectrum. Surgery is among the most valuable forms of labor on the planet, but it's far too scarce and expensive - due to an exceptionally long training pipeline and highly concentrated expertise. We’re building the first surgeon that scales: one system that can acquire, refine, and transfer surgical skills across millions of procedures. v1 is already learning to perform surgical tasks autonomously from demonstrations, and improve from its own experience. Lots of great folks behind us! @BoxGroup, Reveille VC, Constellation, @forward_deploy, @Valkyrie_vc, @DiscipulusVent, @maniacvc + more
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Here are some of the behind the scenes for the F.02 Decommission To be clear: we actually trained our robots to jump autonomously, shipped them to Finland, and had them leap into a vat of molten steel
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Pokémon Go gave Niantic a lot of data.
Introducing the Places Library 📚 A collection of 100 high-fidelity, real-world 3D environments built for embodied AI. Instantly access real-world 3D environments as simulation-ready USDZ files, ready to use in NVIDIA Isaac Sim, Isaac Lab, and compatible OpenUSD simulators. 🔗 Read more: nianticspatial.com/blog/intr… 👉 Download free sample scenes: nianticspatial.com/embodied-… #EmbodiedAI #Robotics #PhysicalAI #Real2Sim #IsaacSim #AI #USDZ
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Mr V retweeted
It’s about to get really crazy, if you are not funding or developing tech in this area, it’s the only true self defense. It was about this time in the last century that the people alive at the time started feeling the dread of WWII. The cycle is reiterating.
We’re launching the Army of Robots. In 2022, we launched the Army of Drones. Today, drones account for over 95% of battlefield strikes, and Ukraine has more than 700 UAV manufacturers. Now we need the next technological breakthrough: the robotization of warfare. The goal is simple — save lives. Robots should take on the most dangerous missions: evacuating the wounded, delivering ammunition, mining and demining, reconnaissance, defending positions and engaging targets. The Army of Robots is not one company. It’s an ecosystem. We will invest in defense tech companies, launch our own technology projects, test them with the military and scale what works on the battlefield. We’re now looking for defense tech companies and engineers working on robotic technologies — as well as a CTO / Tech Lead for the Army of Robots. Join us: thearmyofrobots.com/en
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We’re launching the Army of Robots. In 2022, we launched the Army of Drones. Today, drones account for over 95% of battlefield strikes, and Ukraine has more than 700 UAV manufacturers. Now we need the next technological breakthrough: the robotization of warfare. The goal is simple — save lives. Robots should take on the most dangerous missions: evacuating the wounded, delivering ammunition, mining and demining, reconnaissance, defending positions and engaging targets. The Army of Robots is not one company. It’s an ecosystem. We will invest in defense tech companies, launch our own technology projects, test them with the military and scale what works on the battlefield. We’re now looking for defense tech companies and engineers working on robotic technologies — as well as a CTO / Tech Lead for the Army of Robots. Join us: thearmyofrobots.com/en
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Mr V retweeted
I was going through an Electrical Electronics course some months ago from the US Department of Defense thats specifically for the US Airforce command 1/10
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Mr V retweeted
18 months ago, I went all in on studying biology. I started by building a lab in my apartment (worms!) and later joined one at UCSF. Meanwhile, models were making advances in the virtual world, but in the lab — they fell short. We started C5R to fix this. See more below!
In 12 weeks, we built a research facility that is run entirely by AI. AI designs, executes, and observes experiments end-to-end across biology, chemistry, and materials science. We’re introducing SciUniverse: a benchmark that measures AI’s ability to do real-world scientific research.
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Mr V retweeted
Elon Musk
@elonmuskSep 24
Replying to @vasalex93
1. We will keep accelerating. Our AI efforts are only 3 years old, vs 6 and 10 years old for Anthropic and OpenAI. If our second derivative remains strong, SpaceX will reach pole position in about 6 months. 2. Once you far exceed the caliber of intelligence needed for a class of tasks, additional intelligence is pointless. You don’t need (and it would be cruel to put) Newton-level intelligence in your toaster! 3. Hardware is hard. Bringing massive compute online rapidly is incredibly difficult. SpaceX has demonstrated exceptional ability in this regard and will only get better.
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