Dan Murfitt

Software engineer, tech geek, fair weather photographer and occasional blogger. Views are my own.

[Gary Vaynerchuk @garyvee]

People are yearning for more "real life." Running clubs, hiking tours, ski instructing... it's just so clear to me the explosion of analog.

2036 is going to feel like 2065, and because of that, the opportunity is to build businesses that feel like 1965

[Dan Murfitt @danmurf]

@PovilasKorop I don’t really see this as any different from building an MVP. It’s rough around the edges, but helps gauge interest. Then when things get serious, tidy it up and do it properly.

[Dan Murfitt @danmurf]

This actually sounds amazing.

[jack @jack]

https://t.co/WFWSz5jEpc

[Dan Murfitt @danmurf]

@mehulmpt I was really hoping this would be available through my Ollama plan but it’s extra usage credits only 😢

[Dan Murfitt @danmurf]

I sort of miss that 2023 AI video atheistic https://t.co/4ecv9RbYCR

[Jensen Huang @JensenHuang]

Attackers have frontier AI. Defenders need a frontier AI ecosystem—the best open and closed models, force-multiplied by a global community.

During the Hugging Face incident, closed AI blocked essential forensics. An open-weight frontier model helped contain the intrusion.

That’s why we created the Open Secure AI Alliance.

[Dan Murfitt @danmurf]

@ollama "We’re quickly working on adding capacity to expand access."

Does this mean it will eventually be available through the subscription plan rather than extra usage credits?

[Kimi.ai @Kimi_Moonshot]

Meet Kimi K3

[ollama @ollama]

Token usage beginning to tip towards open models.

Ollama’s @jmorgan and Peter Fenton predict that a supermajority of tokens in the future will be from open models.

[Aravind Srinivas @AravSrinivas]

Imagine a fable 5 quality model that’s 3-4x less expensive in less than 6 months. And an Opus 4.8 grade model that can run on a local device in less than 12 months. Greater than 50% chance that these events will happen. Worth keeping in mind when you make predictions about the future.

[Peter Steinberger 🦞 @steipete]

"When intelligence is plentiful, volition is valuable. The people who are going to make a difference are not the ones who seek relaxation and passively use AI to work less. They are the ones who will seek improvement and actively wrestle with AI to develop their own mental capabilities and accomplish more." https://t.co/gDEy4aABwo

[Mike Bradley @MikeBradleyAI]

Watch us make Local AI the default

[Dan Murfitt @danmurf]

When I spoke to people about Claude Tag, I noticed they initially couldn’t see the difference from the legacy Claude for Slack integration. It sort of reminded me of the release of the Wii U and the confusion people had with the previous Wii.

[Matthew Berman @MatthewBerman]

> mythos is so good at cyber it can't be released

also

> mythos can't detect 20k fraudulent chinese accounts attacking it

[Greg Brockman @gdb]

GPT-5.6 Sol preview — it's a good model:

[Ornith @ornith_]

Aloha! 🌺 Meet Ornith-1.0, a family of open-source LLMs specialized for agentic coding.

Ornith-1.0 spans the full parameter sizes including 9B Dense, 31B Dense, 35B MoE, and 397B MoE. It achieves state-of-the-art performance among open-source models of comparable size on coding benchmarks including:
✅Terminal-Bench 2.1(77.5)
✅SWE-Bench(82.4 on verified, 62.2 on pro, 78.9 on Multilingual)
✅NL2Repo(48.2)
✅SWE Atlas(41.2 on QnA, 42.6 RF, 39.1 TW)
✅ClawEval(77.1)

Post-trained on top of gemma4 and qwen3.5, Ornith-1.0 employs a novel self-improving training strategy in which reinforcement learning is used to generate not only solution rollouts, but also the task-specific scaffolds that drive those rollouts. By jointly optimizing the scaffold and the resulting solution, the model generate higher-quality solutions in agentic coding.😎

All models are released under the MIT license, enabling full commercial and research use.

📖Tech Blog: https://t.co/qT9N2HYWFn
🤗Huggingface: https://t.co/PRrwqjeBtM

[Victor M @victormustar]

some genius invented a kebab benchmark for llms

[Mitchell Hashimoto @mitchellh]

Got em. I poison my AGENTS.md (and other things like code comments) all over the place with prompt injections like this to find people who don't review their code and sling it off to another human. Catches folks all the time and then its an instant ban.

As I've said, I don't care if you don't review your own code. But if you're submitting code to an OSS project and crossing a human boundary, it is simple courtesy to do some human review.

[Cline @cline]

We've kept hearing how GLM-5.2 beats Opus 4.8, and are skeptical of benchmarks - so we tested them on a real bug from the Cline repo. While both models fixed the issue, GLM was the winner in terms of cost and code quality:

- GLM used twice as many tokens (GLM 1.1m vs Opus 660K) but cost half as much (GLM $0.41 vs Opus $0.81)

- Opus finished quicker - 1.6 min and 12 tool calls vs GLM 4.7 min and 28 tool calls

- GLM cleaned up dead code and verified the build compiled before completing. Opus didn't - it left type errors that passed tests but broke the production build.

Both runs used the same Cline harness prompting and tools, so it seems GLM is RL trained to spend more tokens verifying its work before completing. Impressive work by the @Zai_org team!

[Emad @EMostaque]

There will be an open source fable-level model that runs on a base MacBook mini / Air or equivalent.

I don’t think people have realised this.