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My super early impressions of OpenClaw vs Hermes Agent: Hermes seems WAY more reliable at executing actual tasks - even on GPT 5.4. It also feels way more stable. And I absolute love that it shows which tools it's calling as it's executing a task. I also really like that the personality with GPT 5.4 is FAR better on Hermes as well - after a bit of tweaking. With OpenClaw, I was finding it impossible to get GPT 5.4 to stop talking like a sycophantic idiot. On Hermes, I can get it to be direct & push back with little effort. I'm also finding that GPT 5.4 is FAR more reliable on Hermes vs OpenClaw (thanks @heyitsyashu for the tip). It really does feel like Opus 4.6 level performance on OpenClaw, but with even better execution on long-running tasks. Not sure what the Hermes team has done (I'm not technical at all), but it's obvious that the way they've constructed the back-end is far easier for LLMs to figure out what they should be doing. Because of OpenAI oauth being allowed, Hermes + GPT 5.4 os now EASILY the best intelligence per $ 'AI brain' for Agents. I think the @openclaw team needs to deeply study @NousResearch and what they've done because it can likely benefit MASSIVELY. Gut tells me OpenClaw has become FAR too bloated and FAR too 'jack of all trades, master of none'. When it comes to actual execution of tasks, Hermes feels WAY better equipped, and TBH I wouldn't be surprised AT ALL if it becomes adopted by actual businesses/operators at a far greater rate than OpenClaw. I'm also starting to really worry that the days of OAUTH with 3rd party tools is coming to a screeching halt very soon. I don't think OpenAI is going to allow their oauth tokens to be used on an AI agent competitor when they've invested a lot of money on OpenClaw's creator. What I think is gonna end up happening is OpenAI will stop allowing oauth use for 3rd party apps all together (including OpenClaw) and they'll likely release their own OpenClaw v2 to try and compete against Hermes/Computer/CC. Hope I'm wrong, but these tools are far too powerful to be "allowed" to be open source + heavily subsidized tokens, especially as the public outcry re: AI's cost to electricity continues intensifying. But this will give way for ultra-capable, ultra-efficient opensource models that will give 90%+ Opus 4.6/GPT 5.4 performance for 1/10th of the cost that are SPECIALIZED for agentic harnesses like OpenClaw/Hermes. It's starting to get REALLY interesting, folks.
Lots of people asking whatβs so good about computer use. Hereβs 5 things that come to mind 1. operate Mac Apps without a great API: Slack, Google Sheets, Notes, IMessage without installing separate plugins. It instantly transforms all your apps into tools 2. If you need to operate your browser more visually it works really smoothly and fast (good for sites that are still human centric) 3. It uses its own cursor, keyboard etc so you can keep working. 4. Once you do any task once you can simply ask Codex to reflect on what it did and how it would accomplish the task next time with the benefit of hindsight and create a skill AND schedule an automation. Itβs really nice that codex can just schedule and edit automations when asked! itβs very Claw like in this way. This last point is not computer use specific but is powerful when combined with computer use 5. The UI polish is insane: you get nice icons for any application you want to tag into computer use plus all the other built in new stuff like built in file viewer and browser so there is no context switching. So you can iterate really fast and not lose focus. Because of the polish it also feels nice and delightful to use.
Seriously stop everything you are doing and use codex desktop app new computer use. Absolutely mind blowing
We conducted cyber evaluations of Claude Mythos Preview and found that it is the first model to complete an AISI cyber range end-to-end. π§΅ https://t.co/gd9hi0Ve55
Grok 4.20 Reasoning just took the #1 spot on the BridgeBench reasoning benchmark. π₯ Beating GPT-5.4, Claude Opus 4.6, Google Gemini and others. Week after week, Grok keeps climbing across benchmarks. π https://t.co/WnBNrvbQdV
The #MLSys2026 program is out, and it is awesome! π 107 research papers + 28 industry papers spanning the full AI systems stack π Three exciting contests: AWS Trainium programming, Google graph scheduling, and NVIDIA AI kernel generation π€ Keynotes from an outstanding lineup: Amin Vahdat (Google) on infra; @LukeZettlemoyer (UW & Meta) on models; @kozyraki (Stanford & NVIDIA) on architecture; Lidong Zhou (Microsoft) on systems; and @marksaroufim (GPUMode) on GPUs and kernels. Join us in Bellevue, WA in a month! Early registration ends April 19 β donβt miss it: https://t.co/trj383wuVB.
AI is transforming software development, but more code means more pull requests, more edge cases, and more QA pressure on engineering teams. Tusk, a Y Combinator startup, catches bugs that slip past both AI agents and humans using AI-enabled tests based on real production traffic. Built on Amazon Bedrock, Tusk flags issues before code merge so teams can focus on building great products.
What happens when you put competing neural networks in a Petri Dish and start changing the rules while they adapt? Last year we released Petri Dish NCA, where neural nets are the organisms that learn during simulation. Today we're releasing Digital Ecosystems: a browser-based platform for interactive artificial life research. The setup: several small CNNs share a 2D grid, each seeing only a 3x3 neighborhood. No global plan. They compete for territory by attacking neighbours and defending against incoming attacks, learning via gradient descent online while the simulation runs. What we didn't expect was the role of the learning itself. Gradient descent isn't just optimising each species' strategy. Instead, it acts to stabilize the whole system during simulation. Species that overextend get pushed back by the loss. Species that stagnate get nudged to grow. This means you can push parameters toward edge-of-chaos regimes: a zone characterised by emergent complexity. Letting the neural networks learn acts to hold the complex system together while you explore and interact. The platform lets you steer all of this interactively. You can draw walls to create niches, erase parts of the system online, and tune 40+ system parameters to explore the most interesting configurations. We find it mesmerizing to watch species carve out territories and reorganise when you perturb them. Everything runs client-side in your browser, no install needed. Blog: https://t.co/qOuelxmd6l Code: https://t.co/pz7ktDCRZS
NVIDIA releases Lyra 2.0 on Hugging Face A framework for generating persistent, explorable 3D worlds at scale by solving spatial forgetting and temporal drifting in long-horizon video generation. https://t.co/M9kYHhIJ6c
π¨ We're giving roboticists a major upgrade to their vision systems! Today, we announced the launch of the @Stereolabs3D ZED X Nano: a compact, wrist-mount stereo camera engineered for the next generation of robotic manipulation. βBuilding on Stereolabs leadership in AI vision and perception solutions, the ZED X Nano allows us to go deeper into the industrial and robotics markets to win new sockets that require smaller form-factor placements,β said Ouster CEO Angus Pacala.

btw you can ssh into your Mac mini from Claude code desktop now
@benvargas My PR is super stale and I've been working on higher priority stuff. Let me try to get this out by Friday.