Welcome to the first issue of Rushing Robotics with brief overviews of each section.
Weekly Piece of Future #3
Posted in futurism, robotics/AI
Category: robotics/AI – Page 1,097
In a stunning development, a neural network now has the intuitive skills of a 9-year-old.
Also weighing in with an online essay was the Rev. Russell Moore, formerly head of the Southern Baptist Convention’s public policy division and now editor-in-chief of the evangelical magazine Christianity Today. He confided to his readers that his first sermon, delivered at age 12, was a well-intentioned mess.
“Preaching needs someone who knows the text and can convey that to the people — but it’s not just about transmitting information,” Moore wrote. “When we listen to the Word preached, we are hearing not just a word about God but a word from God.”
“Such life-altering news needs to be delivered by a human, in person,” he added. “A chatbot can research. A chatbot can write. Perhaps a chatbot can even orate. But a chatbot can’t preach.”
“OpenAI was created as an open source (which is why I named it ‘Open’ AI), non-profit company to serve as a counterweight to Google, but now it has become a closed source, maximum-profit company effectively controlled by Microsoft,” Musk tweeted (Opens in a new window) today. “Not what I intended at all.”
OpenAI this week acknowledged that its process for “fine-tuning” ChatGPT is “imperfect.”
“Sometimes the fine-tuning process falls short of our intent (producing a safe and useful tool) and the user’s intent (getting a helpful output in response to a given input),” OpenAI says (Opens in a new window). “Improving our methods for aligning AI systems with human values is a top priority (Opens in a new window) for our company, particularly as AI systems become more capable.”
Generative AI on Roblox
Posted in robotics/AI
Today, Roblox provides creators with a platform that enables end-to-end tools, services, and support to help them build the most immersive 3D experiences. With Roblox Studio, creators have everything they need, out-of-the-box and for free, to build their experiences and publish immediately on all popular platforms, reaching 61 million people daily worldwide. With the advent of generative AI techniques, however, we are seeing an opportunity to revolutionize creation on the platform, both by augmenting Roblox Studio to make creation dramatically faster and easier, and also by enabling every user on Roblox to be a creator.
As we all know, generative AI learns the underlying patterns and structures of data and generates new content, such as images, audio, code, text, 3D models, or other forms of media, that have not been seen before. With a dramatic acceleration in these tools’ effectiveness for everyday content creation, this technology is at an inflection point. It now has the capability to capture the creator’s intent, provide a broad range of digital editing capabilities, help create the content, and allow for fast iteration. We have already heard from Roblox creators about how they are using this technology to create. However, these off-the-shelf AI systems are not integrated with our platform and they often do not produce “Roblox ready” output that requires substantial follow on work from a creator. We see an incredible opportunity to build generative AI tools and APIs focused on Roblox.
Read more about Generative AI on our official blog: https://blog.roblox.com/2023/02/generative-ai-on…ture-of-creation/
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Roblox’s mission is to bring the world together through play. We enable anyone to imagine, create, and have fun with friends as they explore millions of immersive 3D experiences, all built by a global community of developers.
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And, what BingGPT needs to figure out before it can replace traditional search engine.
Large language models still struggle with basic reasoning tasks. Two new papers that apply machine learning to math provide a blueprint for how that could change.
‘We’ve put together the top 10 technology trends to watch out for in 2023 that will help enterprises be future-ready and build resilience within their organisation to thrive in any new normal,’ Kalyan Kumar, Chief Technology Officer and Head of Ecosystems of HCL Tech said in a release.
“I think I’m probably just as guilty as everybody else,” Toyota Research Institute’s (TRI) senior vice president of robotics, Max Bajracharya, admits. “It’s like, now our GPUs are better. Oh, we got machine learning and now you know we can do this. Oh, okay, maybe that was harder than we thought.”
Ambition is, of course, an important aspect of this work. But there’s also a grand, inevitable tradition of relearning mistakes. The smartest people in the room can tell you a million times over why a specific issue hasn’t been solved, but it’s still easy to convince yourself that this time — with the right people and the right tools — things will just be different.
In the case of TRI’s in-house robotics team, the impossible task is the home. The lack of success in the category hasn’t been for lack of trying. Generations of roboticists have agreed that there are plenty of problems waiting to be automated, but thus far, successes have been limited. Beyond the robotic vacuum, there’s been little in the way of breakthrough.
Say you have a cutting-edge gadget that can crack any safe in the world—but you haven’t got a clue how it works. What do you do? You could take a much older safe-cracking tool—a trusty crowbar, perhaps. You could use that lever to pry open your gadget, peek at its innards, and try to reverse-engineer it. As it happens, that’s what scientists have just done with mathematics.
Researchers have examined a deep neural network—one type of artificial intelligence, a type that’s notoriously enigmatic on the inside—with a well-worn type of mathematical analysis that physicists and engineers have used for decades. The researchers published their results in the journal PNAS Nexus on January 23. Their results hint their AI is doing many of the same calculations that humans have long done themselves.
The paper’s authors typically use deep neural networks to predict extreme weather events or for other climate applications. While better local forecasts can help people schedule their park dates, predicting the wind and the clouds can also help renewable energy operators plan what to put into the grid in the coming hours.