Demis: Solving erdos problems are far from true invention
Demis Hassabis argues that solving Erdős problems, while mathematically significant, falls short of demonstrating true scientific invention or reasoning.
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Demis Hassabis argues that solving Erdős problems, while mathematically significant, falls short of demonstrating true scientific invention or reasoning.
Reddit speculation on AI company cash burn and market consolidation by 2027, predicting funding scarcity for non-GAFAM players.
Also covered by r/OpenAI
Developer built iOS/watchOS app and landing page using Claude Code, reached 1,500+ users by solving friction in law enforcement location-sharing workflows.
Google DeepMind agent solved 9 of 353 open Erdős problems autonomously, costing ~$100-300 per problem.
https://preview.redd.it/b9kl1t77743h1.png?width=955&format=png&auto=webp&s=6ae0f4ac116e08ce619765b6674144961058a689 https://preview.redd.it/ls5oh1be743h1.png?width=416&format=png&auto=webp&s=0e2899df9ef0d704cb5da08b1916f6009ac18b37 Yes, I am absolutely…
[Drive Link for Zipped Proof](https://drive.google.com/file/d/1qU_LyLY-JMhNR_bqOV1-a2RJAbplL68e/view?usp=drivesdk) I am a developer and paying long term subscriber to ChatGPT since January 2025. I build complex local first sovereign systems. My workflows are incredibly…
My parents tech literacy is bad. They will have me check clear as day scam emails and the likes out way too damn often. To save my sanity, I finally used Claude Code to create a solution, hopefully.... Heck, even if it helps a bit, I will be happy. Not a 100% for sure thing…
Developer refactored 120-file FastAPI service using DeepSeek V4 and Hunyuan with 80x cost savings vs Opus; open-weight models matched Opus latency but introduced production bugs.
Elon Muks's xAI has gone all in on natural gas, while SpaceX is obsessed with orbital data centers. What happened to the "solar-electric economy" he promised?
Joint Energy-Based Models isolate discriminative vs. generative objective effects on human visual alignment using controlled architecture experiments.
AI weather models converge on similar atmospheric representations; evidence suggests they solve particle-like physics despite differing architectures.
RaNNDy uses fixed random weights in hidden layers for transfer operator approximation, reducing training cost via closed-form output layer solution.
CVSearch training-free framework for multimodal LLMs adaptively balances visual search strategies to improve high-resolution image perception efficiency.
Fine-tuning LLMs for entity resolution in KYC via structure-guided matching across naming conventions and scripts.
Scheduling algorithms for aircraft disassembly optimization with task precedence and certification constraints.
Study of training sample requirements for neural network inverse kinematics in robotic manipulators.
that meme on the chatgpt subreddit is so spot on ngl. even when you have requirements locked down managing the stack gets so weird. claude is an absolute beast at backend logic, teh reasoning depth is just insane now.the real mess starts when u try to scale past a basic landing…
Tokenisation is an integral part of the current NLP pipeline. Current tokenisation algorithms such as BPE and Unigram are greedy algorithms -- they make locally optimal decisions without considering the resulting vocabulary as a whole. We instead formulate tokeniser…
The Flexible Job Shop Scheduling Problem (FJSP) is the optimal allocation of a set of jobs to machines. Two primary challenges persist in FJSP: the unpredictable arrival of future jobs and the combinatorial complexity of the problem, rendering it intractable for conventional…
Large language models (LLMs) increasingly excel at mathematical reasoning, but their unreliability limits their utility in mathematics research. A mitigation is using LLMs to generate formal proofs in languages like Lean. We perform the first large-scale evaluation of this…
Autonomous systems have achieved superhuman performance in isolation or simulation, yet they remain brittle in shared, dynamic real-world spaces. This failure stems from the dominant single-agent paradigm for physical applications, where other actors are ignored or treated as…
Self-policy distillation via subspace projection isolates task-relevant capabilities from style/formatting without external curation signals.
[Start Screen](https://preview.redd.it/d59wc985ai2h1.png?width=1433&format=png&auto=webp&s=dc4e557bc499159a7d2b0048802204a7a933e39d) Just sharing what came out of a weekend. My son (10) and his cousin (10) love games and asked me if they can "make a game", since…
OpenAI's GPT-next model solved the 80-year-old Erdős planar unit distance conjecture computationally for under $1000, demonstrating AI capability in pure mathematics.
Comparative evaluation of coding agents (GitHub Copilot, Pi, Claude Code, OpenCode) using Qwen 3.6 27B isolates model vs. harness performance.
Hobbyist trains DCGAN on 350 iPod Touch 4 photos of a red solo cup to study sensor artifacts.
Let’s unpack what Demis Hassabis said at the end of yesterday’s Google I/O keynote. This is Optimizer, a weekly newsletter sent from Verge senior reviewer Victoria Song that dissects and discusses the latest gizmos and potions that swear they're going to change your life. This…
OpenAI claims its reasoning model disproved a geometry conjecture unsolved since 1946 — and this time, the mathematicians who exposed its last embarrassing claim are backing it up.
OpenAI's general-purpose model autonomously solved the planar unit distance problem, a famous 80-year-old Erdős conjecture, discovering new constructions outperforming grid-based solutions.