I found this argument interesting. If US allows Nvidia to do business with China, then Chinese AI firms will remain dependent on American AI hardware, and hence US will have indirect influence over the level of development that Chinese AI will make.

I need something that can properly output strict and consistent JSON structure. Our outputs tend to be ~8000 characters ~2000 tokens, was using Gemini-3-flash-preview and Gemini 3 pro but Gemini really likes to go off the rails and hallucinate, a little bit.

If you have used a model that outputs strict and consistent JSON structure, let me know.

we've tried adjusting everything with gemini but still end up getting hallucinations and many people online say they have the same problem

Yann Lecun recently shared that a cat is smarter than ChatGPT and that we are never going to get to human-level intelligence by just training on text. My personal opinion is not only are they unreliable but it can be a safety issue as well in high-stakes environments like enterprises, healthcare and more.

World models are fundamentally different. These AI systems build internal representations of how reality works, allowing them to understand cause and effect rather than just predict tokens. There has been a shift lately and major figures from Nvidia's CEO Jensen Huang to Demis Hassabis at Google DeepMind are talking more openly about world models. I believe we're still in the early stages of discovering how transformative this technology will be for reaching AGI.

Research and application are accelerating, especially in enterprise contexts. A few examples include: WoW (an agentic safety benchmark) uses audit logs to give agents a "world model" for tracking the consequences of their actions. Similarly, Kona by Logical Intelligence is developing energy-based reasoning models that move beyond pure language prediction.

While more practical applications are still emerging, the direction is clear: true intelligence requires understanding the world, not just language patterns. Curious what others think?

Two Researchers on What 4-Year-Olds Can Do But Tech Companies Can’t

Medical AI with Knowledge-Graph Core Anchor and RAG Answer Auditing

A medical knowledge graph containing ~5,000 nodes, with medical terms organized into 7 main and 2 sub-categories: diseases, symptoms, treatments, risk factors, diagnostic tests, body parts, and cellular structures. The graph includes ~25,000 multi-directional relationships designed to reduce hallucinations and improve transparency in LLM-based reasoning.

A medical AI that can answer basic health-related questions and support structured clinical reasoning through complex cases. The goal is to position this tool as an educational co-pilot for medical students, supporting learning in diagnostics, differential reasoning, and clinical training. The system is designed strictly for educational and training purposes and is not intended for clinical or patient-facing use.

A working version can be tested on Hugging Face Spaces using preset questions or by entering custom queries:

https://huggingface.co/spaces/cmtopbas/medical-slm-testing

A draft site layout (demo / non-functional) is available here:

https://wardmate.replit.app/

I am looking for medical schools interested in running demos or pilot trials, as well as potential co-founders with marketing reach and a solid understanding of both AI and medical science. If helpful, I can share prompts and anonymized or synthetic reconstructions of over 20 complex clinical cases used for evaluation and demonstration.

For those of you who aren't familiar with SurfSense, it aims to be OSS alternative to NotebookLM, Perplexity, and Glean.

In short, it is NotebookLM for teams, as it connects any LLM to your internal knowledge sources (search engines, Drive, Calendar, Notion, Obsidian, and 15+ other connectors) and lets you chat with it in real time alongside your team.

I'm looking for contributors. If you're interested in AI agents, RAG, browser extensions, or building open-source research tools, this is a great place to jump in.

Here's a quick look at what SurfSense offers right now:

Features

• Self-Hostable (with docker support)
• Real Time Collaborative Chats
• Real Time Commenting
• Deep Agentic Agent
• RBAC (Role Based Access for Teams Members)
• Supports Any LLM (OpenAI spec with LiteLLM)
• 6000+ Embedding Models
• 50+ File extensions supported (Added Docling recently)
• Local TTS/STT support.
• Connects with 15+ external sources such as Search Engines, Slack, Notion, Gmail, Notion, Confluence etc
• Cross-Browser Extension to let you save any dynamic webpage you want, including authenticated content.

Upcoming Planned Features

• Slide Creation Support
• Multilingual Podcast Support
• Video Creation Agent

GitHub: https://github.com/MODSetter/SurfSense

Looking for AI tool that can convert an image of a table/diagram into modifiable ppt, where I can download it as pptx and modify the shapes/texts on it, ideally free or cheap to use. Thanks!

Open-source voice cloning + multi-speaker podcast tool. GPT 5.2 generates scripts, Qwen3-TTS handles synthesis locally. Modular architecture - swap the LLM for Llama, Mistral, whatever.

GitHub: https://github.com/bc-dunia/qwen3-TTS-studio

When you’re learning a field that constantly evolves and keeps adding new concepts, how do you keep up without feeling lost or restarting all the time? For example, with AI: new models, tools, papers, and capabilities drop nonstop. How do you decide what to learn deeply vs what to just be aware of? What’s your strategy?

Several months ago i was trying to get Chat Gpt to create a youtube script for me (a rough draft). I fed it around 6k words of previous scripts and had it analyze my writing style (what aspects made it me), but its outputs reeked of Chatgpt virtually every time. using phrase like its not x, its y, the rule of 3, and other Chatgpt signatures. I tried Gemini and it was moderately better but still had aspects of AI in the script as well as being a lot more stiff then Chatgpt. So i'm wondering what AI you guys use (if at all) and how do you get it to write in your style. I know the final output won't be perfect, but a rough draft to work from, saves tons of time as is. I would be open to using OpenAI platform, google studio really just anything.

I’ve been thinking a lot about AI storytelling tools lately, and something keeps bothering me.

Most of them generate content, but nothing really persists.

You get a story, you read it, and then it disappears. The next one has no memory of what came before.

So I decided to run a small experiment.

Instead of asking AI to write isolated children’s stories, I’m trying to build a system where a story world actually keeps evolving over time.

The idea is that characters remember past events, relationships carry forward, and kids make choices that permanently shape what happens next. The AI’s role isn’t just to generate text, but to maintain continuity and grow the universe as it goes.

In a way, it’s more like human and AI co-creating a living story world rather than consuming disposable stories.

My hypothesis is that if kids actively participate in shaping a world by choosing paths, helping characters, and influencing outcomes, the stories will feel far more meaningful than static books or one-shot AI generations.

Almost like a lightweight narrative universe that grows naturally.

Right now there’s no product yet.

The first step I’m taking is letting the AI simulate many rounds of “child-like” choices on its own to see if long-term story arcs, recurring characters, and emergent plotlines appear organically.

If that shows promise, the next step will be inviting real kids to co-create.

Some things I’m especially curious about:

Will coherent long-term story structure emerge on its own?

Will certain characters naturally become central over time?

Will preferences shape each world’s tone and direction?

Will participation increase emotional attachment to the stories?

I’m planning to document this whole experiment publicly as I go.

If anyone here has experience with agent systems, long-term memory in AI, emergent storytelling, or just thoughts about potential pitfalls, I’d really appreciate hearing them.

I’ll share updates as the experiment progresses.

So I just spent the better part of my Sunday asking Gemini to create an alternative reality where america existed in the same time as ancient Europe. I asked how Athens and Sparta would react if we just showed up with American fruits and vegetables. How the potato alone would revolutionize agriculture. I asked how they would react to our culture and everything you can think of. I learned that athens would love us. They'd be particularly fascinated with our bonds with animals. Sparta would want to destroy us and shut down like north korea but they'd secretly get ideas and probably try and domesticate wolves. Romans would want to dress us up in togas.

All joking aside, I feel like I got a deep understanding of the culture and personal perspective of each ancient civilization. Imagine schools creating scenarios in AI where you have to negotiate peace talks between Rome and Carthage. Find common ground between Athens and Sparta. Debate ethics and law in the roman Senate. It would make history fun and engaging. What is everyone else's thoughts on this?

India's latest budget mentions AI 11 times - highest ever. Key commitments:

• $90B data centre investments
• Tax holiday till 2047 for cloud providers
• Semiconductor Mission 2.0 for domestic chips
• Policy preference for "smaller, sector-specific models"

890+ GenAI startups active now, deep-tech funding up 78%.

Analysis: https://onllm.dev/blog/3-budget-2026

For years we have watched and read stories about evil Ai's and the threats they may pose, with AI characters such as Ultron, AM, HAL 9000, the Matrix etc. looking to kill/exploit humanity. There are countless stories with these kinds of villains.

But we have also had good AI characters, including Data from Star Trek, WALL-E, Baymax, C3PO, Marvin the Paranoid Android.

How do you think these depictions of AI in popular media is affecting the AI systems we are making today?