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LLMs have been able to make good success in coding, because someone is reviewing the work it produces (code). Ofcourse quality of code has become better over time. IMO other than Human-in-the-loop scenarios, AI will not see huge adoption in businesses.

What could be the reason to nerf?

This does not scale well for enterprises. The risk always-on agents bring is something no one wants to take. Guardrail and Harness is going to be next big thing for Enterprise AI.

Are there "good" Open source Decision models built on Gemma-4 and also trainiable on own data?

the maker - https://peterslab.co/products/twitter-web-viewer

I tend to agree with this observation. I started taking my evening calls (6:30 to 10:30 PM everyday) from my terrace in open air and my overall fatigue became quite less and I feel quite less tired compared to earlier time when I used to take these calls from my room.

Neither Nvidia nor xAI owns those chips on paper. Valor, the shell company holds legal title.

https://x.com/BullTheoryio/status/2061029970236133554

Claude keeps launching automation products but not sure if they are bothering about quality. I was using claude cowork and was hoping to get simple tasks done using web browser. It is unreliable and often fails

I have used voice mode on chatgpt, Gemini, Grok as I use it while driving. Best is from openAI. Natural conversation, smarter and meaningful replies.

So pelican must have become the mandatory test case to pass for all model providers before launch.

I have been looking forward to build something like this using open models. A voice assisstant I can talk while I am driving, as I do have long commute. I do use chatGPT voice mode and it works great for querying any information or discussions. But I want to do tasks like browsing web, act like a social media manager for my business etc.

Microservices created the need for more teams, devs, coordination, meetings, scrum teams, scrum master, Jira, CI CD tools, cloud market and so on.. It is very well planned :)

The explanation of "hallucination" is quite simplified, I am sure there is more there.

If there is one problem I have to pick to to trace in LLMs, I would pick hallucination. More tracing of "how much" or "why" model hallucinated can lead to correct this problem. Given the explanation in this post about hallucination, I think degree of hallucination can be given as part of response to the user?

I am facing this in RAG use case quite - How do I know model is giving right answer or Hallucinating from my RAG sources?

Thanks. sorry, asking more question - Do we need human in the loop with Cube to define the views for all kinds of queries.

In my use case, it's going to be exposed to various kind of stakeholders and there will be versatility of user queries. I can't pre-create views/aggregations for all scenarios.

Currently exploring cube for a "natural language to SQL" solution.

My schema is - 90+ Tables, 2500+ Columns, well documented

From your experience, does Cube look a fit? My use cases will definitely have JOINS.

How people are unearthing knowledge from ancient libraries using Claude

https://x.com/PrintedPathways/status/1865637416637231406

This looks great, thanks for building this.

Something on similar lines which many may link, Research Rabbit - https://www.researchrabbit.ai/

Can we give reference of these articles to LLMs and get them to write articles like this for educational contents and produce similar WebGL graphics code to render images. I mean, just use this style and produce educational content using AI. that might make the studies more interesting.

Can we give reference of these articles to LLMs and get them to write articles like this for educational contents and produce similar WebGL graphics code to render images. I mean, just use this style and produce educational content using AI. that might make the studies more interesting.

I fear that in the goal of going from "manual coding" to "fully automated coding", we might end up in the middle, where we are "semi manual coding" assisted by AI, which would need different software engineer skill.

Is it possible to build similar to anthropic computer use feature with Qwen vision model.

Someone open sourced it with langchain

https://x.com/1littlecoder/status/1856397375704576399

Great, congrats on your launch.

1. Does it take care of Bot detection. Most sites will have it.

2. Is this something similar to Firecrawl - https://www.firecrawl.dev/

Honest question - Why use interfaces like this, but not regular HTML client?

I fear that in the goal of going to "manual coding" to "fully automated coding", we might end up in the middle, where we are "semi manual coding" assisted by AI which needs different software engineer skill.

Many are there, apart from what others mentioned I am exploring Anything LLM - https://anythingllm.com/. Liked the workspace concept in it. We can club documents in workspaces and RAG scope is managed.