Data-driven Decision Making

Can you name the three most famous Impressionist artists? Or describe the color palette and techniques that define Color Field Painting or Naive Art? Your ability to answer these questions will have a big impact on your experience with text-to-image generators like Midjourney. But what if you haven’t been to art school or spent years studying art history? Continue Reading →

Meta, the company formerly known as Facebook, has open-sourced LLAMA 2, its advanced AI model. Zuck might be onto something here. Let's explore what LLAMA 2 brings to the table, its potential applications, and the implications of this open-source move for the AI community at large. Continue Reading →

China has laid out a blueprint for regulating generative AI – technology that powers chatbots like OpenAI’s ChatGPT and Google’s Bard. Overseen by the Cyberspace Administration of China, the new regulations set parameters on the public use of AI. The law instructs Chinese AI systems to adhere to "core socialist values," which raises some interesting questions. Continue Reading →

Large Language Models (LLMs) are transforming the way we interact with technology. These models, developed by leading tech companies such as OpenAI, Replicate, Cohere, Hugging Face, and Anthropic, to name a few, are pushing the boundaries of what's possible in natural language processing. Here's a short overview of the most popular LLMs from these companies, exploring their unique capabilities and best use cases. Continue Reading →

Welcome to the brave new world of generative AI, where the machines are no longer just number crunchers, they’re word crunchers, image crunchers, audio and video crunchers. But here’s the catch: If we’re to ride the wave of this technological revolution, we need to rethink not just the tools we use, but also how we use them. Continue Reading →

At a dinner party the other night, a very accomplished business person told a story about how he and his wife were certain that their devices were listening to their conversations. “I was talking to my wife about a pair of designer shoes that she wanted to purchase, and not 10 minutes later while she was doing some online research for work, she saw an ad for that exact pair of shoes. She hadn’t searched for the shoes; the ad just appeared. Clearly, our computers or our phones are listening.” Some people nodded in agreement, and others began to chime in. Continue Reading →

You've probably read about the "existential threat" posed by Artificial General Intelligence (AGI). It's a dark future where super-intelligent machines outsmart us and cause humanity to go extinct. We may be mesmerized by this high-stakes narrative, but we’re also being misled. The real threats of AI are already here, lurking in our everyday digital experiences. While tech titans and the media tout a dystopian AI future, they’re drawing our attention away from the AI and related data privacy issues we need to solve right now. Continue Reading →

The Office of Science and Technology Policy (OSTP) is asking for your help. The Biden-Harris Administration is developing a National Artificial Intelligence (AI) Strategy that will chart a path for the United States to harness the benefits and mitigate the risks of AI. To inform this strategy, OSTP requests public comments to help update U.S. national priorities and future actions on AI. Continue Reading →

Shelly Palmer talks about the "Alignment Problem" - one of the scariest and most dangerous issues posed by AI. When you set a goal for an autonomous agent (such as AutoGPT, AgentGPT or BabyAGI) will the output be aligned with your goal and human values? The answer today is, "no so much." What will this look like as more and more people start to rely on generative AI, LLMs, and Autonomous Agents? Continue Reading →

A machine learning algorithm called CEBRA is unlocking the hidden structure in neural code, with the potential to revolutionize brain-machine interfaces (BMIs). The algorithm can be used to decode what a mouse sees while watching a movie, predict primate arm movements, and reconstruct the positions of rats as they roam. The research, led by Mackenzie Mathis, EPFL’s Bertarelli Chair of Integrative Neuroscience, was published in Nature. Continue Reading →