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Baidu just dropped an open-source multimodal AI that it claims beats GPT-5 and Gemini
Baidu Inc., China’s largest search engine company, released a new artificial intelligence model on Monday that its developers claim outperforms competitors from Google and OpenAI on several vision-related benchmarks despite using a fraction of the computing resources typically required for such systems.
The model, dubbed ERNIE-4.5-VL-28B-A3B-Thinking, is the latest salvo in an escalating competition among technology companies to build AI systems that can understand and reason about images, videos, and documents alongside traditional text — capabilities increasingly critical for enterprise applications ranging from automated document processing to industrial quality control.
What sets Baidu’s release apart is its efficiency: the model activates just 3 billion parameters during operation while maintaining 28 billion total parameters through a sophisticated routing architecture. According to documentation released with the model, this design allows it to match or exceed the performance of much larger competing systems on tasks involving document understanding, chart analysis, and visual reasoning while consuming significantly less computational power and memory. — Read More
Common Ground between AI 2027 & AI as Normal Technology
AI 2027 and AI as Normal Technology were both published in April of this year. Both were read much more widely than we, their authors, expected.
Some of us (Eli, Thomas, Daniel, the authors of AI 2027) expect AI to radically transform the world within the next decade, up to and including such sci-fi-sounding possibilities as superintelligence, nanofactories, and Dyson swarms. Progress will be continuous, but it will accelerate rapidly around the time that AIs automate AI research.
Others (Sayash and Arvind, the authors of AI as Normal Technology) think that the effects of AI will be much more, well, normal. Yes, we can expect economic growth, but it will be the gradual, year-on-year improvement that accompanied technological innovations like electricity or the internet, not a radical break in the arc of human history.
These are substantial disagreements, which have been partially hashed out here and here.
Nevertheless, we’ve found that all of us have more in common than you might expect. — Read More
From Words to Worlds: Spatial Intelligence is AI’s Next Frontier
In 1950, when computing was little more than automated arithmetic and simple logic, Alan Turing asked a question that still reverberates today: can machines think? It took remarkable imagination to see what he saw: that intelligence might someday be built rather than born. That insight later launched a relentless scientific quest called Artificial Intelligence (AI). Twenty-five years into my own career in AI, I still find myself inspired by Turing’s vision. But how close are we? The answer isn’t simple.
Today, leading AI technology such as large language models (LLMs) have begun to transform how we access and work with abstract knowledge. Yet they remain wordsmiths in the dark; eloquent but inexperienced, knowledgeable but ungrounded. Spatial intelligence will transform how we create and interact with real and virtual worlds—revolutionizing storytelling, creativity, robotics, scientific discovery, and beyond. This is AI’s next frontier. — Read More
Google says new cloud-based “Private AI Compute” is just as secure as local processing
Google’s current mission is to weave generative AI into as many products as it can, getting everyone accustomed to, and maybe even dependent on, working with confabulatory robots. That means it needs to feed the bots a lot of your data, and that’s getting easier with the company’s new Private AI Compute. Google claims its new secure cloud environment will power better AI experiences without sacrificing your privacy.
The pitch sounds a lot like Apple’s Private Cloud Compute. Google’s Private AI Compute runs on “one seamless Google stack” powered by the company’s custom Tensor Processing Units (TPUs). These chips have integrated secure elements, and the new system allows devices to connect directly to the protected space via an encrypted link.
Google’s TPUs rely on an AMD-based Trusted Execution Environment (TEE) that encrypts and isolates memory from the host. Theoretically, that means no one else—not even Google itself—can access your data. Google says independent analysis by NCC Group shows that Private AI Compute meets its strict privacy guidelines. — Read More
The Transactional Graph-Enhanced LLM: A Definitive Guide to Read/Write Chatbots for Relational Data
The integration of Large Language Models (LLMs) with enterprise relational databases has been largely confined to read-only Retrieval-Augmented Generation (RAG) systems. This paper transcends that limitation, presenting a comprehensive architectural framework for building conversational AI agents capable of both reading and writing to a relational database via a Knowledge Graph (KG) intermediary. We will dissect the core architectural challenge, evaluate multiple design patterns — including KG as a cache, KG as a source of truth, and a sophisticated Command Query Responsibility Segregation (CQRS) pattern. This document provides an exhaustive, production-ready guide, complete with data modeling strategies, detailed prompt engineering for both query and command generation, Mermaid architecture diagrams, and best practices for security, validation, and transaction management. This is the blueprint for creating the next generation of truly interactive, data-manipulating chatbots. — Read More
Data Science Is Not Dying…. It Is Splitting Into Five New Jobs You Should Know
When I first fell in love with data, it felt simple and dangerous at the same time.
You could load a CSV… run a few queries… make a chart… and suddenly people listened.
That was twelve years ago. The tools have changed… the expectations have widened… and the word data scientist now means something else depending on the team you join.
…Data science is not going away. It is multiplying into new craft roles that require different muscles.
If you treat this moment like doom… you will be outpaced.
If you treat it like a chance to pick what you are really good at… you will be in demand. — Read More
AI Turns Brain Scans Into Full Sentences and It’s Eerie To Say The Least
In a dark MRI scanner outside Tokyo, a volunteer watches a video of someone hurling themselves off a waterfall. Nearby, a computer digests the brain activity pulsing across millions of neurons. A few moments later, the machine produces a sentence: “A person jumps over a deep water fall on a mountain ridge.”
No one typed those words. No one spoke them. They came directly from the volunteer’s brain activity.
That’s the startling premise of “mind captioning,” a new method developed by Tomoyasu Horikawa and colleagues at NTT Communication Science Laboratories in Japan. Published this week in Science Advances, the system uses a blend of brain imaging and artificial intelligence to generate textual descriptions of what people are seeing — or even visualizing with their mind’s eye — based only on their neural patterns. — Read More
Google’s Ironwood TPUs represent a bigger threat than Nvidia would have you believe
Look out, Jensen! With its TPUs, Google has shown time and time again that it’s not the size of your accelerators that matters but how efficiently you can scale them in production.
Now with its latest generation of Ironwood accelerators slated for general availability in the coming weeks, the Chocolate Factory not only has scale on its side but a tensor processing unit (TPU) with the grunt to give Nvidia’s Blackwell behemoths a run for their money. — Read More
Kimi K2 Thinking
Today, we are introducing KimiK2Thinking, our best open-source thinking model.
Built as a thinking agent, it reasons step by step while using tools, achieving state-of-the-art performance on Humanity’s Last Exam (HLE), BrowseComp, and other benchmarks, with major gains in reasoning, agentic search, coding, writing, and general capabilities.
… K2 Thinking is now live on kimi.com under the chat mode [1], with its full agentic mode available soon. —Read More
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