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"successful people create companies. more successful people create countries. the most successful people create religions." - qi lu

the cult-ish vibes of openai and sam altman, specifically, could be due to this foundational business aspiration.

imo he is suggesting that people should create profoundly impactful things akin to religion. i am not religious myself but i do appreciate it. it's more of a plus to society as a whole. also everyone has their own "delusions" so pick your poison. mine happens to be 2045.

metaphorically, i don't care if openai is a cult and sam altman is the shaman. i'm sure as hell performing my rituals everyday.

Unless we're mindful of controlling it and using it for good, there's nothing wrong about the technology

https://youtu.be/0bd4NLlfutE?si=50rIIQ2yweM6GGtP

Sam Altman was recently on the All-In podcast

He mentioned that he may not even call the model GPT5 and that there is no fixed timeline currently -

https://reddit.com/link/1cq58i4/video/cjgxhuqs7zzc1/player

All the key takeaways from the discussion (no sign up)

Here is a one minute rundown of the latest AI news:

• GPT2-chatbot returns: im-a-good-gpt2-chatbot & im-also-a-good-gpt2-chatbot has appeared on the LMSYS arena battle, reports suggest this is better than every current public available model
• AlphaFold3: Google DeepMind has released AlphaFold3, a revolutionary model with expectations to speed up drug discovery and unlock secrets of diseases.
• CIA AI Model: Microsoft created a secure, offline AI for the CIA. Nicknamed "Project Guardian," this AI analyses classified data without internet risks, offering a potential game-changer for US intelligence.
• TikTok new AI labelling tool: Tiktok recently pushed out some new AI labelling tools that will automatically detect content made by tools such as DALLE-3
• OpenAI to face Google: Sources suggest OpenAI will release a search engine tool similar to perplexity, to possibly dethrone google and revolutionise search

Read more (No sign up required) -

Long form version (GPT2-Chatbot)

Is there any chance we could 1. democratically control AI systems and 2. have full control over our own data? And this be the dominant model.

Are these bad ideas? Why? What’s a better one? How can we brace against the storm. What is the optimal strategy?

If we did identify something akin to an optimal strategy, could it be implemented and would it engage the public sufficiently?

It feels like it’s all there, if only it could be pieced them together.  

Episodic memory recall represented as traveling neural activation over the cortex

I hope that Meta Yann LeCun, Google Jeff Dean, Microsoft Mustafa Suleyman, OpenAI Sam Altman and other important players in the AI space don't just go all in on Transformers but have some efforts exploring a broader set of architectures, especially biologically inspired -- otherwise they may miss the AGI boat!

LLMs are powerful and it may be possible to build AGI-like systems using AgenticAI wrappers around them, but LLMs have some fundamental limitations and are unlikely to yield real world general intelligence.

How about going back to the drawing board with inspirations from recent neuroscience findings? With the vast computing power now available, it is time to revisit biologically plausible approaches to AI like spiking neural networks, local learning, local rewards, continuous learning, sparsity, and so on. Though computationally intensive, these methods may be practical now and are more likely to have the right characteristics to achieve hashtag#AGI. Currently efforts in hashtag#neuromorphic hardware are going nowhere because we haven't developed the right algorithms to run on them.

See a blog post that lists LLM limitations - https://medium.com/p/54e4831f4598

Over the past few years, I have developed and implemented multiple novel architectures to understand what facets of biological neural networks are important to implement and which are not. That is the most important question to answer while exploring the space of possible biologically inspired architectures and algorithms. I have many unpublished results that I'd like to publish as time permits.

Video: Episodic memory recall represented as traveling neural activation over the cortex.

The following guide looks forward to what new developments we anticipate will come for AI programming in the next year - how flow engineering paradigm could provide shift to LLM pipelines that allow data processing steps, external data pulls, and intermediate model calls to all work together to further AI reasoning: From Prompt Engineering to Flow Engineering: 6 More AI Breakthroughs to Expect

• LLM information grounding and referencing
• Efficiently connecting LLMs to tools
• Larger context sizes
• LLM ecosystem maturity leading to cost reductions
• Improving fine-tuning
• AI Alignment

Being an abstract thinker and not an engineer, my concept is that the main difference between human intelligence and the AI is that we are a continuous process, while the current LLMs are but a series of sparks. You write a prompt, hit enter and it comes alive... for a few seconds and then it dies. You put another prompt and another spark is born, one that analyzes the previous response and creates a continuation.

I've seen a video where AI was connected to a 2D video game, each agent operated to one character, and after a while they started their social life, one of them threw a party, they were even going to hold elections, if I remember correctly.

So, are there works on creating a continuous process with a power of a big LLM?

We are not prepared for the next model. My prediction is that they have an absolute monster behind the scenes but do not want to unleash it just yet as the chaos that would ensue

P.S. if your into the latest AI news, insights and tips Swing by https://mapleai.beehiiv.com  if you wanna join the fun and stay ahead!

https://reddit.com/link/1cilbdt/video/1ku8s9emr1yc1/player