📰 AI for Investment Decisions in 2026: How Gen Z Uses Chatbots Despite Trust Gaps
AI for investment decisions is gaining traction among Gen Z and millennials, yet experts warn of significant risks due to lack of regulation and potential misinformation. While half of Americans expect AI to replace financial advisors, trust remains ...
📰 Why Martin Lueck (Aspect Capital) Says AI Can’t Replace Human Traders in 2026
Quant pioneer Martin Lueck, co-founder of Aspect Capital, cautions against surrendering trading decisions to artificial intelligence, echoing concerns amid industry shifts toward machine-driven systems. His warnings come as peers like Cliff Asness embrace ...
📰 DeepSeek-V4 (2026): Open-Source LLM Outperforms GPT-4 on Huawei Cloud — Now Live
DeepSeek-V4, the latest reasoning-optimized large language model, has been officially released with Huawei Cloud as its first partner to deploy the model. The model sets new benchmarks in efficiency and agentic performance....
📰 Sovereign AI Merger: Cohere and Aleph Alpha Launch $20B Transatlantic Powerhouse (2026)
Sovereign AI tie-up: Cohere and Aleph Alpha are advancing merger talks to create a $20 billion transatlantic AI powerhouse, aiming to challenge US and Chinese dominance with Europe-backed, data-sovereign models....
An Indian med student asked AI how to make money.
AI said: create a MAGA influencer. Conservative men are loyal spenders.
He did. 10M views per Reel. 👇
https://chat-to.dev/view_trend?id=Ym54S01GU3I1aXNPTkVyMzVtUFpyQT09&redirect=/trends
📰 AI Defense Spending Surges in 2026: $5.5B in 10 Days to Autonomous Systems & Nuclear Tech
AI and defense companies dominate US growth investment as capital floods into autonomous systems, nuclear modernization, and cyber warfare sectors, while other industries struggle to secure funding....
📰 7 Companies Thriving in Turbulent Times: AI-Driven IT and Software Wins in 2026
Despite widespread software stock volatility, a new wave of IT companies is thriving by embracing AI-driven agility and co-innovation models. These firms are outpacing legacy players by abandoning rigid roadmaps in favor of real-time adaptation....
Every developer who has worked with long context models knows the feeling. You paste in your codebase, add your requirements, & somewhere around the halfway point the model starts forgetting things it read at the top.
This is called the performance cliff and it is the real problem with long context AI, not the number itself. DeepSeek-V4 is making a specific claim that it stays useful across that entire window
https://firethering.com/deepseek-v4-open-source-million-token-context/
Every developer who has worked with long context models knows the feeling. You paste in your codebase, add your requirements, include some examples, and somewhere around the halfway point the model starts forgetting things it read at the top. You get generic answers. It misses files it already saw. The context window is technically full but the model is functionally half-asleep. This is called the performance cliff and it is the real problem with long context AI, not the number itself. DeepSeek-V4 is making a specific claim here. Not just that it supports 1 million tokens, several models do that now. The claim is that it stays useful across that entire window by fundamentally changing how attention works at scale. In the 1M token setting, V4-Pro requires only 27% of the compute per token and 10% of the KV cache compared to DeepSeek-V3.2. It is MIT licensed. Weights are on HuggingFace right now. And they shipped two models simultaneously, which means there is an actual choice to make depending on what you are building.
📰 DeepSeek V4 (2026): The Open-Source AI Model Beating OpenAI and Anthropic in Coding
DeepSeek has unveiled a preview of its new AI model, V4, claiming it can match leading closed-source systems from US rivals. The open-source model shows significant gains in coding capability, reigniting global AI competition....
📰 5 Red Flags of ChatGPT Financial Advice in 2026 (Avoid Costly Mistakes)
As AI chatbots like ChatGPT become popular for financial guidance, experts warn of hidden risks. Relying on generative AI for money decisions can lead to flawed recommendations, hidden biases, and serious financial consequences....
AI Haberleri 🤖
MrB33n
Firethering