Jeff 🇺🇸/acc

Stanford’s 2025 Robotics Review talks about the rise of the “electronic workforce,” where robots go beyond factories and start thinking, optimizing, and making calls on their own. We’re taking that next step with VOLM, turning idle AI + robotics power into onchain, yield-gen autonomous systems. AI learning + sensor data + blockchain incentives = machines that actually create value. Pretty much expanding Stanford’s vision into a real, scalable, autonomous economy. Source: setr.stanford.edu/technology/rob…

@MHermez92 the app is currently in closed beta. in 1-2 weeks, it will be available for desktop download, and we’ll also have a live version running directly on the website. to fast-track this process, another engineer will be joining the core team soon

@destinyiskind could you please demonstrate how does your platform work? is there any platforms live yet?

Volm is live on Base. appreciate the love

i wanted to actually show the exact stack we built at volm to make this happen. this is our core data-to-yield pipeline and honestly it is pretty wild how these layers stack up. 🧵⤵︎

Engineering excellence is not about relying on the processing power of server infrastructure. It is about optimizing hardware constraints to transform idle capacity into sustainable economic value.

DSA or advanced mathematics may not be directly applied in everyday tasks; rather, they function as cognitive training that strengthens abstract reasoning, problem decomposition, and adaptability to future, yet-unknown paradigms and technological shifts.

The future of robotics is here, and it’s mind-blowing 🤯 We’re looking back at 2025’s most futuristic demo: drones controlled entirely by thought. Watch @_okdara_ explain the tech → goo.gle/3N5ndSw

@PeterDiamandis AI needs robots to be the economy

We’ve just published the @VolmLabs Whitepaper. If you’ve been wondering what we’re really building, this explains it best. whitepaper drive.google.com/file/d/1xtubgS…

Ensuring privacy is critical, as IoT discovery is a known vulnerability. Stanford researchers note: “Privacy is often missing in IoT discovery protocols; devices broadcast info in the clear, exposing users to profiling and tracking.” Full research: iot.stanford.edu/pubs/PrivateIo…

Had a good time at BaseCamp with the @BuildOnBase community. Conversations with fellow developers were inspiring and pushed me to shape a bolder vision for Volm, building the most open and composable layer for the physical AI economy. Stay tuned.

BaseCamp was a good event, full of valuable conversations and insights. ✌️

An impressive achievement from Colorado State University. These nature inspired, shape shifting robots push the boundaries of hardware, while demonstrating just how much depends on sophisticated software, AI, and control algorithms. This is an exciting development with the potential to revolutionize countless fields, from search and rescue to industrial inspection. The future is in adaptable systems.

> GPT-5 is the first series of models that actually doesn’t hallucinate basically at all *real-world utility-maxxing instead of benchmark-maxxing intensifies* Disclaimer: GPT-5 is still not perfect and may make (far fewer now) mistakes

going to try live-tweeting the GPT-5 livestream. first, GPT-5 in an integrated model, meaning no more model switcher and it decides when it needs to think harder or not. it is very smart, intuitive, and fast. it is available to everyone, including the free tier, w/reasoning!

A Survey of Context Engineering for Large Language Models +160 pages the most important research you really have to read this! arxiv.org/pdf/2507.13334 arxiv.org/abs/2507.13334

Suggested Further Reading/Watching Video recordings and reports from Stanford HAI’s Summit youtube.com/watch?v=LhEfJ5… AI education programs from the University of Michigan, CSU, and others Student Perspectives on the Benefits and Risks of AI in Education (May 2025) arxiv.org/abs/2505.02198… Analyzing the Impact of AI Tools on Student Study Habits (Sep 2024) arxiv.org/abs/2412.02166… 7/7

Conclusion: Strategic Imperatives + AI presents the potential for a paradigm shift in education: reducing the administrative burden on educators, enabling more substantive pedagogical interactions, and providing personalized learning experiences for every student. However, realizing this potential is contingent upon the following strategic imperatives: Pedagogical Reform: A fundamental redesign of curricula and teaching methodologies is required. Equitable Deployment: Distribution models that ensure AI solutions reach every student without discrimination must be prioritized. Human-in-the-Loop Approach: AI must be an augmentation tool that empowers human educators, rather than replacing them. Ethics and Governance: Robust governance mechanisms and ethical boundaries must be established to protect data privacy, transparency, security, and the cognitive depth of learning. 6/7

AI Integration in Education: A Human-Centered and Responsible Paradigm Shift 1. Symposium Background and Technical Framework The 2025 AI+Education Summit, organized by the Stanford HAI (Human-Centered AI Institute) on February 25, 2025, was themed "Human-Centered AI for a Thriving Learning Ecosystem." Throughout the symposium, the integration of artificial intelligence technologies into educational systems was subjected to an in-depth analysis, examining both its technological affordances and inherent ethical risks. 1/7