Lexicon Labs

AGI In Your Pocket: The Future of Lean, Mean, Portable Open-Source (Ph.D. Level) LLMs NEWSFLASH  January 29, 2025 – A breakthrough at UC Berkeley’s AI lab signals a seismic shift in artificial intelligence. PhD candidate Jiayi Pan and team recreated DeepSeek R1-Zero’s core capabilities for just $30 using a 3B-parameter model, proving sophisticated AI no longer requires billion-dollar budgets (Pan et al., 2025). This watershed moment exemplifies how small language models (SLMs) are reshaping our path toward artificial general intelligence (AGI). From Lab Curiosity to Pocket-Sized Powerhouse The Berkeley team’s TinyZero project achieved what many thought impossible: replicating DeepSeek’s self-verification and multi-step reasoning in a model smaller than GPT-3. Their secret weapon? Reinforcement learning applied to arithmetic puzzles. Key Breakthrough: The 3B model developed human-like problem-solving strategies: - Revised answers through iterative self-checking - Broke dow...

The Future of Large Language Models: Where Will LLMs Be in 2026? The rapid evolution of large language models (LLMs) has reshaped the AI landscape, with OpenAI, DeepSeek, Anthropic, Google, and Meta leading the charge. By 2026, advancements in hardware, algorithmic efficiency, and specialized training will redefine performance benchmarks, accessibility, and real-world applications. This post explores how hardware and algorithmic improvements will shape LLM capabilities and compares the competitive strategies of key players. The Current State of LLMs (2024–2025) As of 2025, LLMs like OpenAI’s GPT-5 , Google’s Gemini 1.5 Pro , and Meta’s Llama 3.1 dominate benchmarks such as MMLU (multitask accuracy), HumanEval (coding), and MATH (mathematical reasoning). Key developments in 2024–2025 highlight critical trends: Specialization: Claude 3.5 Sonnet (Anthropic) leads in coding (92% on HumanEval) and ethical alignment. Multimodality: Gemini integrates text, images, and audio, ...