According to DeepLearning.AI, Alibaba has released several advanced AI models, including Qwen3-235B-A22B-Instruct-2507, a reasoning-enabled Thinking-2507 version, and the 480-billion-parameter Qwen3-Coder, all under the Apache 2.0 license. The Instruct model outperformed other non-reasoning models on 14 out of 25 benchmarks, while the Thinking variant achieved mid-tier results. These open-sourced models offer enhanced reasoning and coding capabilities, which can improve algorithmic trading, on-chain data analysis, and smart contract development for crypto traders and developers. The large-scale release is expected to intensify AI model competition, potentially lowering barriers for crypto market participants leveraging AI-driven trading strategies. Source: DeepLearning.AI

According to @AnthropicAI, recent research indicates that large language model (LLM) personalities are shaped during training, and 'emergent misalignment' can result from unexpected influences in training data. The team investigates whether persona vectors can be used to counteract these effects, potentially reducing risks of unpredictable AI behavior. For crypto traders, advancements in AI alignment could impact algorithmic trading reliability and the development of AI-driven trading bots, as trustworthy AI models are critical for market forecasting and automated strategy execution (source: @AnthropicAI).

According to Anthropic (@AnthropicAI), the newly formed Anthropic Economic Advisory Council will provide strategic analysis on how artificial intelligence affects labor markets and economic growth. This move aims to deliver actionable insights for investors and traders by assessing AI-driven shifts in workforce dynamics and potential growth sectors, which could directly influence related equities and crypto markets tied to AI advancement (source: Anthropic Twitter, April 28, 2025).