The Cloudflare CEO joined to talk about standing up to content scraping, the internet's potential futures, and his company's relationship to Trump. Matthew Prince may not be a household name, but the world most certainly knows his work. Prince is the cofounder and CEO of Cloudflare . Launched in 2010, the internet infrastructure company has found itself increasingly in the position of serving as the web's bodyguard. It filters out bad traffic, keeps sites safe, and stops them from crashing when too many people visit. Its tools defend against DDoS attacks. In 2017, Cloudflare made headlines when it dropped white supremacist site The Daily Stormer . Cloudflare's severing of ties with The Daily Stormer marked a momentous shift, one that came after years of claiming a neutral stance. Prince continues to evolve the way Cloudflare works. In July, the company rolled out a new tool tasked with blocking unauthorized AI scraping. It effectively creates a pay-per-crawl model requiring AI platforms to shell out money if they want access to a site's content. On this episode of, I talked to Prince about publishing, the old internet, and how his ideal version of the future web means that OpenAI just might become the Netflix of content. KATIE DRUMMOND: Good to have you here, Matthew. You should have been warned ahead of time, but you probably weren't.

We propose and study Complementary Concept Generation (CCGen): given a concept of interest, e.g., "Digital Cameras", generating a list of complementary concepts, e.g., 1) Camera Lenses 2) Batteries 3) Camera Cases 4) Memory Cards 5) Battery Chargers. CCGen is beneficial for various applications like query suggestion and item recommendation, especially in the e-commerce domain. To solve CCGen, we propose to train language models to generate ranked lists of concepts with a two-step training strategy. We also teach the models to generate explanations by incorporating explanations distilled from large teacher models. Extensive experiments and analysis demonstrate that our model can generate high-quality concepts complementary to the input concept while producing explanations to justify the predictions.

Always has been, always wi– Wait, what? Every company seeks to expand beyond its core market, both to satisfy shareholders as well as grow its sales opportunities. Intel has spent a lot of time and money over the years trying to move beyond processors alone and test the waters as a consumer brand. You could see the evolution: the Intel chime (dumdumdumDUM!), the dancing bunny people, the expansion into various parts of the PC… and beyond. Intel's core business, though, has always had an underlying goal: sell more chips.

Thank you for reading my latest article Beyond The Hype: What You Really Need To Know About AI In 2023. Here at LinkedIn and at Forbes I regularly write about management and technology trends. To read my future articles simply join my network here or click'Follow'. Also feel free to connect with me via Twitter, Facebook, Instagram, Slideshare or YouTube. By now, it's probably clear to most people that artificial intelligence is going to have a fairly large impact on our lives.

By now, it's probably clear to most people that artificial intelligence is going to have a fairly large impact on our lives. A few years ago, you might have been forgiven for wondering whether it was just another fad. But recent advances – such as the emergence of generative AI tools like ChatGPT – have left most of us in no doubt that we're witnessing the dawn of a new era. An era that's likely to see our lives change just as dramatically as we saw with the arrival of personal computers, the internet, or smartphones. Perhaps even more so – Google CEO Sundar Pichai famously stated back in 2016 that it would have a bigger impact than fire or electricity.

The story of 2022 was the emergence of AI, first with image generation models, including DALL-E, MidJourney, and the open source Stable Diffusion, and then ChatGPT, the first text-generation model to break through in a major way. It seems clear to me that this is a new epoch in technology. To determine how that epoch might develop, though, it is useful to look back 26 years to one of the most famous strategy books of all time: Clayton Christensen's The Innovator's Dilemma, particularly this passage on the different kinds of innovations: Most new technologies foster improved product performance. I call these sustaining technologies. Some sustaining technologies can be discontinuous or radical in character, while others are of an incremental nature. What all sustaining technologies have in common is that they improve the performance of established products, along the dimensions of performance that mainstream customers in major markets have historically valued.

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In an effort to streamline the process of diagnosing patients with multiple sclerosis and Parkinson's disease, researchers used digital cameras to capture changes in gait – a symptom of these diseases – and developed a machine-learning algorithm that can differentiate those with MS and PD from people without those neurological conditions. Their findings are reported in the IEEE Journal of Biomedical and Health Informatics. The goal of the research was to make the process of diagnosing these diseases more accessible, said Manuel Hernandez, a University of Illinois Urbana-Champaign professor of kinesiology and community health who led the work with graduate student Rachneet Kaur and industrial and enterprise systems engineering and mathematics professor Richard Sowers. Currently, patients must wait – sometimes for years – to get an appointment with a neurologist to make a diagnosis, Hernandez said. And people in rural communities often must travel long distances to a facility where their condition can be assessed.

With technology continuing to move on at a swift pace, there's been plenty of recent discussion as to whether digital renders can truly ever replace product photography. Taking this one step further, is it possible that one day, artificial intelligence could simply create images without needing any input from a photographer or digital artist at all? As photographers, we often marvel at how amazing modern technology can be, how magical that new "must-have" camera feature is, or how smart the image-processing software has become. I don't consider myself to be especially old, but when I think back to using a manual-focusing 35mm SLR (because that's all we had to use, not because I'm a hipster) and compare that experience to the incredible face detection or eye detection autofocus on modern mirrorless cameras, it's hard to believe these huge technological advances have happened within my lifetime. Even the act of sitting in my living room, controlling the lighting and home entertainment with my voice, or video-calling a friend in another country on an iPad are literally things that my child self would have considered science fiction.

Nope, we're not talking about Einsteinian physics or tesseracts, those theoretical four-dimensional objects that rotate, mind-bending, along two planes at once. These Four Ds are imminently practical, and they're already shaping the information infrastructure around which we build our businesses and reshaping the future of business IoT. Each of the Four Ds--as conceived by Asteria CEO Pina Hirano--is a pillar of a successful digital ecosystem, which is itself the platform on which tomorrow's businesses will stand or fall. As you explore these ideas, think about how they could apply to your operation--or the new business you're considering building atop this cutting-edge of information technology. With all due respect to spacetime and advanced mathematics, then, here are the Four Ds of the future that every business operator needs to master.