DeepReach AI

Still thinking about the Physical AI / robotics meetup we hosted in San Jose this week. We had 3× more people register than we could accommodate. Researchers, founders, and investors working on world models, robotics, and real-world AI showed up. One thing became very clear during the conversations: The biggest bottleneck for robotics right now isn’t just better models. It’s real-world deployment and data. Robots need environments to learn, tasks to execute, and systems that can actually run them in production. This is exactly the problem space we’re working on at DeepReach. Feels like the Physical AI era is just getting started. #PhysicalAI #Robotics #EmbodiedAI #WorldModels #DeepTech

ABB + NVIDIA Omniverse is an important signal. But it also highlights a bigger problem: Robotics doesn’t have a hardware problem. It has a deployment problem. Most automation is built for large factories. The real opportunity is SMB manufacturing, where robots must be: lightweight affordable fast to deploy Physical AI will scale through data and deployment engines, not just better robots. #Robotics #PhysicalAI #EmbodiedAI #Automation #DeepTech

The "iPhone moment" for Embodied AI is happening now. 🤖 We're hosting a deep-dive robotics mixer next Thursday (5-7 PM) at the HireIO South Bay office. Focus: ✅ Scaling Robot Foundation Models ✅ Hardware/Software Co-optimization ✅ Global Commercialization Limited capacity for high-signal dialogue. Apply here: luma.com/4sujx58e

DeepReach has been accepted into the @nvidia Inception program! In January, our ARR doubled — deploying robots into real environments and training them to perform concrete tasks. Thanks to our clients, investors, and partners for the continued support. #Robotics #PhysicalAI #NVIDIAInception #EmbodiedAI #RealWorldAI #NVIDIA #Startup

The very first step of VLA data collection

Deploying to our first customer! A huge warehouse in Los Angeles. #Robotics #labor

@oyhsu Hah that’s exactly what we help

#unitree #CES26 team came to our event at demonstrating G1’s amazing moves. #robot

Our founder @drxcliu shares the bottleneck of robot deployment and our vision to help robot companies run task reliably at client sites nationwide.

@cb_doge that’s ambitious.

ELON MUSK: xAI and Google will be the only real contenders at the top of AI in the long run.

@xai wow

Our first hoodie is out!

@0xmitsurii He was already a billionaire that time with IPO. But still respect

Nobody cares untill you are rich. Xiaomi's founder then vs now.

@elonmusk @elonmusk check the necklace 👀 clear proof of OAI trying to distill from @Gemini or stealing it’s data

Hmm

Stanford just pulled off something wild 🤯 They made models smarter without touching a single weight. The paper’s called Agentic Context Engineering (ACE), and it flips the whole fine-tuning playbook. Instead of retraining, the model rewrites itself. It runs a feedback loop write, reflect, edit until its own prompt becomes a living system. Think of it as giving the LLM memory, but without changing the model. Just evolving the context. Results are stupid good: +10.6% better than GPT-4 agents on AppWorld +8.6% on finance reasoning 86.9% lower cost and latency The trick? Everyone’s been obsessed with clean, minimal prompts. ACE shows the opposite: long, dense, self-growing prompts win. Fine-tuning was about changing the model. ACE is about teaching it to change *itself.* This isn’t prompt engineering anymore. It’s prompt evolution.

@StartupArchive_ @TimLi_DR

Keith Rabois: “I tell founders not to worry about runway. Worry about lift.” “If you think about lift in a plane context, a company is only valuable if you achieve lift. Runway is a tactic for achieving lift, and you may need to extend the runway so that you have more time to get lift. But unless you’re actually achieving lift with that extra time, it doesn’t help you.” Keith continues: “I hate when a founder is like, ‘I want to raise this much money because it gives me two years runway.’… That is a stupid way to think about your fundraising.” Instead, founders should ask themselves what they need to achieve to achieve lift, and then work backwards from that. When Keith invests at Khosla Ventures and Founders Fund, they write internal memos about the three key risks to the company. Usually you can’t achieve all three in one financing, so founders should be asking themselves, What’s the most important inflection? And then structure their financing to achieve that. Keith advises founders that it’s ok to let their runway go very low if they feel like they’re approaching lift: “A lot of founders get very bad advice like ‘Oh, you need to have this much runway or you won’t be able to raise money from strength.’ That’s nonsense. If you have traction - if you hit a viral coefficient of 1 with three months of runway - almost every VC on the planet knows how to invest in that company, and it will not be a problem.” Video source: @khoslaventures (2024)

Next-gen GEPA. Proved the power of reasoning improvement just with context arxiv.org/abs/2510.04618

@OpenAIDevs Aligned with our vision: eval is more important than ever

Introducing AgentKit—build, deploy, and optimize agentic workflows. 💬 ChatKit: Embeddable, customizable chat UI 👷 Agent Builder: WYSIWYG workflow creator 🛤️ Guardrails: Safety screening for inputs/outputs ⚖️ Evals: Datasets, trace grading, auto-prompt optimization