LLMs
One thing that is still confusing to me, is that we've been building products with machine learning pretty heavily for a decade now and somehow abandoned all that we have learned about the process now that we're building "AI".
The biggest thing any ML practitioner realizes when they step out of a research setting is that for most tasks accuracy has... See more
The biggest thing any ML practitioner realizes when they step out of a research setting is that for most tasks accuracy has... See more
Ask HN: What are some actual use cases of AI Agents right now? | Hacker News
You are assuming that the probability of failure is independent, which couldn't be further from the truth. If a digit recogniser can recognise one of your "hard" handwritten digits, such as a 4 or a 9, it will likely be able to recognise all of them.
The same happens with AI agents. They are not good at some tasks, but really really food at others.
Humans are bad at coming up with search queries. Humans are good at incrementally narrowing down options with a series of filters, and pointing where they want to go next. This seems obvious, but we keep building interfaces for finding information that look more like Google Search and less like a map.
All information tools have to give users some... See more
All information tools have to give users some... See more
thesephist.com • Navigate, don't search
We generally lean towards picking more advanced commercial LLMs to quickly validate our ideas and obtain early feedback from users. Although they may be expensive, the general idea is that if problems can't be adequately solved with state-of-the-art foundational models like GPT-4, then more often than not, those problems may not be addressable... See more
Developing Rapidly with Generative AI
The way that most RLHF is done to date has the entire response from a language model get an associated score. To anyone with an RL background, this is disappointing, because it limits the ability for RL methods to make connections about the value of each sub-component of text. Futures have been pointed to where this multi-step optimization comes at... See more
Nathan Lambert • The Q* hypothesis: Tree-of-thoughts reasoning, process reward models, and supercharging synthetic data
Overview
MaxText is a high performance , highly scalable , open-source LLM written in pure Python/Jax and targeting Google Cloud TPUs and GPUs for training and inference . MaxText achieves high MFUs and scales from single host to very large clusters while staying simple and "optimization-free" thanks to the power of Jax and the XLA compiler.
MaxText... See more
MaxText is a high performance , highly scalable , open-source LLM written in pure Python/Jax and targeting Google Cloud TPUs and GPUs for training and inference . MaxText achieves high MFUs and scales from single host to very large clusters while staying simple and "optimization-free" thanks to the power of Jax and the XLA compiler.
MaxText... See more
google • GitHub - google/maxtext: A simple, performant and scalable Jax LLM!
The need for better AI or LLM-specific infrastructure, along with the host of problems that come with non-deterministic of LLMs, means that there’s more software work ahead of us, not less. Abstraction layers like LLMs create more possibilities and thus, more work.
Is this a good thing or a bad thing? I’m not sure.
A great example of this is frontend... See more
Is this a good thing or a bad thing? I’m not sure.
A great example of this is frontend... See more
Shortwave — rajhesh.panchanadhan@gmail.com [Gmail alternative]
Generative AI can automate simple tasks
By automating simpler, tedious tasks (generating boilerplate code, fixing linter errors, generating unit tests, etc.), generative AI can help engineers focus on more complex tasks.
Generative AI can improve quality & reliability
Since generative AI models are trained on large codebases, they have the potential... See more
By automating simpler, tedious tasks (generating boilerplate code, fixing linter errors, generating unit tests, etc.), generative AI can help engineers focus on more complex tasks.
Generative AI can improve quality & reliability
Since generative AI models are trained on large codebases, they have the potential... See more

