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@engineerrprompt

Building https://t.co/w2mi5UKxJv, Creator of localGPT | AI Educator

Katılım Temmuz 2023
1.3K Takip Edilen2.2K Takipçiler
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Prompt@engineerrprompt·
Yesterday I released the 'preview' of LocalGPT v2, and its already trending on Github Its an opinionated implementation of private RAG powered by local models via @ollama and @huggingface. Give it a ⭐️ on @github (🙏🙏) Watch the video in next post to learn how it was built...
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Claude
Claude@claudeai·
We're extending Claude Fable 5 access on all paid plans, as well as keeping Claude Code’s weekly rate limits 50% higher, through July 19.
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Prompt@engineerrprompt·
AX (Agent Experience) will be more important than DevEx!
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Prompt@engineerrprompt·
@joshwoodward @GeminiApp prototyping an idea within geminiapp and then continuing building it in aistudio. will be great to bring more folks to aistudio
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Josh Woodward
Josh Woodward@joshwoodward·
What's something that you're surprised @GeminiApp can't do well, and we should have fixed a long time ago?
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Prompt@engineerrprompt·
I really like the experiments @databricks ran. The choice of the harness is critical right now. The same model in different harnesses can not only have different performance but also the cost can be substantially different. Simpler harness is better than over-engineered one.
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Matei Zaharia@matei_zaharia

We benchmarked coding agents on our own internal tasks at Databricks and learned a lot! There are many surprising opportunities to lower cost and increase quality, and many models including open source ones are truly competitive now. 🧵

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Prompt@engineerrprompt·
Its better than Fable on Cursorbench because .... >* Grok 4.5 has an advantage on CursorBench: an earlier snapshot of the Cursor codebase was unintentionally included in training. The exact score impact is unclear. That data has been removed for future models. will be testing it shortly.
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Prompt@engineerrprompt·
Looks really interesting. Built on top of Kimi K2.7 (seems like there is alot more performance you can extract from open models with post-training+RL). and 1000 tokens per second!!!!!! Also read the blogpost, interesting details on multi-cluster training.
Cognition@cognition

Introducing SWE-1.7, the most capable model we’ve trained yet. It scores within a few points of the strongest frontier models at a fraction of the cost, and is now available at 1000 tok/s. RL is not hitting its limit: after refining our recipe, we keep seeing gains as we scale

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Prompt@engineerrprompt·
@claudeai can you please also reset the weekly limits?
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Claude
Claude@claudeai·
We're extending access to Claude Fable 5 on all paid plans through July 12.
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Prompt@engineerrprompt·
Really great to see NVIDIA experimenting with novel hybrid architectures for Nemotron family. Its becoming a major western lab! I just posted a video on Nemotron TwoTower (link in next post). Another interesting idea from NVIDIA to push the model throughput without full retraining.
NVIDIA AI@NVIDIAAI

The Nemotron family just passed 100M downloads! Huge thank you to the community building with us and showing what’s possible with open models. Cheers to OSS 🍾

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Prompt@engineerrprompt·
Some thoughts on Fable! As you have probably heard, it does feel like a step change if you use it properly. Some tips from using it over the last few days. Don't use it as a chat model. Give it bigger tasks. Great to use with /goal (RIP your rate limits!). For most bug-fixes, medium effort surprisingly works great. If you are doing architecture design work, use high/xhigh. Be ambitious with your goals and use it for bigger features. Its not a model you want to just use for small bug-fixes. Its great for planning and system design. Use it to generate tasks. Then use other models like Opus 4.8/GPT 5.5 for implementation. Verification with Fable. The orchestrator/executor workflow will push your Fable limits for a lot longer. Update all your codebases with Fable. Ask it to rewrite your claude dot md files. Use it to audit your skills. Its hard to go back to Opus/GPT5.5 once you get a hang of how it works!
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Prompt@engineerrprompt·
@trq212 can you elaborate what the routine means here "some routine tasks like coding and debugging will fall back to Opus 4.8."
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Thariq
Thariq@trq212·
Have seen some questions about the updated classifiers and wanted to clarify. As with the original classifiers, a small fraction of routine coding and debugging tasks will be flagged and fall back to Opus. We're excited for guys to get access back tomorrow.
Anthropic@AnthropicAI

Claude Fable 5 will be available again globally tomorrow. After a series of productive conversations with the US government, we're redeploying the model with a new set of classifiers to target and block more cybersecurity tasks. In the near term, some routine tasks like coding and debugging will fall back to Opus 4.8. We’ll continue to refine these classifiers over the coming weeks to reduce false positives and better distinguish genuine misuse from legitimate requests. We’ve also begun drafting a consensus framework—with Amazon, Microsoft, Google, and other Glasswing partners—for assessing the severity of AI jailbreaks and how AI developers should respond to them. We invite other industry partners and model providers to join us in this effort. Finally, we’re scaling up our collaboration with the US government on model testing and safeguards. This will include pre-release access to models and safeguards for evaluation, information sharing on jailbreaks and misuse, and dedicated resources for joint research. Thank you to our users for your patience, and to our partners across the government, industry, and the research community who worked alongside us to make Fable 5 available again. Read our full blog: anthropic.com/news/redeployi…

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Prompt@engineerrprompt·
@thearslaniqbal We will have to see how "useful" this version of Fable will be. The first version of the classifier was basically blocking anything related to biology. I am curious what this one will do.
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Arslan Iqbal
Arslan Iqbal@thearslaniqbal·
@engineerrprompt That sounds likely. Blocking more risky prompts can also block some good ones by mistake.
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Prompt@engineerrprompt·
This is really interesting. They say "Our testing confirmed that many less capable models—including Claude Opus 4.8, GPT-5.5, and Kimi K2.7—could identify the same vulnerabilities as Fable 5 did in the report." and "The new classifier means that the specific technique described in the Amazon report is blocked in over 99% of cases." I think we are going to see a lot more false positives this time around and will be using Opus 4.8 most of the time :)
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