#78: Enabling the Future of AI (2025)
Making predictions, especially about the future, is famously tricky yet remains a favorite year-end tradition. Antoine de Saint-Exupéry said it well: "Your task is not to foresee the future but to enable it." I believe by choosing the right predictions, we enable the future the way we’d like it to be.
Last year, during the first week of December, Clem Delangue, CEO of Hugging Face and our dearest subscriber, published his predictions for 2024. We shared them and asked you to send us your predictions. We had an amazing response from people like Sara Hooker (Cohere), Yoshua Bengio (Mila), Max Hjelm (CoreWeave), and others. An analysis will follow of which 2024 predictions came to life!
Today, we want to do the same, since Clem was right on time again. And let’s make it into a tradition! Six predictions for AI in 2025 (and a review of how my 2024 predictions turned out):-
- There will be the first major public protest related to AI
- A big company will see its market cap divided by two or more because of AI
- At least 100,000 personal AI robots will be… → tweet link
The only thing we will change this time is that we’re giving you three questions to start with. Our three questions are:
- What paper of 2024 is so significant that it will change 2025? Or what was the paper that surprised you the most?
- What industry will experience the most disruption from AI advancements in 2025?
- What overlooked challenge in AI today will become a major focus in 2025? or What are research areas that are overlooked?
Send us your thoughts – [email protected] – to be featured in the special Predictions Edition of Turing Post!
So, the conversations and actions around reasoning are heating up. In the last two weeks, we’ve been “exposed” to two very promising previews from China: DeepSeek-R1 and Alibaba’s QwQ-32B, both attempting to challenge OpenAI’s o1. Meanwhile, Google’s DeepMind is reportedly developing an AI model with advanced reasoning, leveraging chain-of-thought prompting.
Research Papers from Chinese AI Labs:
1. Shanghai Jiao Tong University and GAIR researchers surpassed OpenAI’s O1-preview in AIME 2024 with a simple distillation method and limited samples. Their model excelled in safety/generalization but relied on the teacher model, urging first-principles research for sustainable AI innovation → read the paper
2. Tsinghua University researchers found LLMs using implicit reasoning skip step-by-step logic, relying on memory/intuition. Probing showed instability and less reliability versus explicit Chain-of-Thought, critical for accurate complex reasoning → read the paper
3. Tsinghua University introduced HiAR-ICL, automating reasoning in In-Context Learning with Monte Carlo Tree Search and "thought cards." HiAR-ICL emphasizes how to think, systematically addressing reasoning challenges via structured automation → read the paper
Additionally, there have been significant developments in various research papers that are reshaping the future of AI. Some of these papers include:
- NVIDIA introduced a block-sparse attention mechanism for Transformer-based LLMs. It uses local/global attention phases to achieve up to 11x inference speedup on sequences up to 1M tokens while retaining 95-100% accuracy → read the paper
- Arizona State University reviewed using LLMs for judgment tasks. They presented a taxonomy of methodologies and applications, highlighting bias, vulnerabilities, and self-judgment, with future directions in human-LLM collaboration and bias mitigation → read the paper
- Google DeepMind’s framework leverages recursive language-based "games" for self-improvement, meeting conditions of feedback, coverage, and scalability. It suggests a roadmap for scalable AI via autonomous data generation and feedback loops → read the paper
You can find the rest of the curated research at the end of the newsletter.
Various articles and experiments have also shed light on the potential and advancements in AI:
- "The Gen AI Bridge to the Future" - Discusses generative AI as the key link between today’s devices and the wearable computing era, enabling transformative, context-aware interactions.
- Dostoevsky Exploration - Explores the dangers of over-rationalization and idol worship, emphasizing unconditional love as a remedy for societal pitfalls.
- "AI Minecraft Experiment Breakthrough" - Showcases LLM-powered agents in Minecraft forming communities, jobs, and even a parody religion.
Google DeepMind revolutionizes 4D content creation and reinvents time-series analysis with visuals - DeepMind's CAT4D framework
Robotics Revolution - Highlights robotics’ “ChatGPT moment,” as AI-driven learning gives robots dexterity and general-purpose capabilities.
