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Category: robotics/AI – Page 1,508

ChatGPT: The AI-powered Chatbot that is equal parts brilliant and terrifying

At number 4 on IE’s list of 22 best innovations is ChatGPT, an AI-powered Chatbot that gained over 1 million registered users in just 5 days after release.

The year 2022 saw a host of brilliant inventions, ranging from the James Webb Space Telescope, the HIV vaccine, and DALL-E, to transparent solar windows. But just when we thought the year had seen its fair share of excellence and innovation, ChatGPT caught us by surprise.

Developed by the OpenAI foundation, an independent research body founded by Elon Musk, the Artificial Intelligence-powered chatbot released on November 30, is everything mind-blowing, bizarre, and daunting. The San Francisco-based company is also responsible for the breakthrough image generator DALL-E 2.

NASA engineer teaches AI to be ‘GPS-like’ to guide astronauts over the lunar surface

An AI system is being developed to lead explorers around the lunar surface.

Without instruments like the GPS we have on Earth, scientists have been attempting for years to figure out how to travel over the lunar surface.

Landmarks like trees or buildings on Earth can serve as fuzzy but useful distance measures-features that are non-existent on the Moon.

NASA/Reese Patillo.

Since the Moon’s atmosphere is significantly thinner than Earth’s, it is challenging to determine the size and distance of distant landmarks when looking at the horizon.

Continue reading “NASA engineer teaches AI to be ‘GPS-like’ to guide astronauts over the lunar surface” | >

Twenty-Five Eye-Opening 2023 Predictions About Generative AI And ChatGPT Including A Splash Of AI Ethics And AI Law Tossed In

Bigger, better, and badder. That’s the overall gist of what is going to happen with Artificial Intelligence (AI) throughout the upcoming year of 2023.

What is going to happen with generative AI and ChatGPT in 2023? Here’s your answer. Filled with lots of helpful background and insights. Start the new year armed with the latest on where AI is heading.

Holding Information in Mind May Mean Storing It Among Synapses

Summary: Findings support modern thought that neural networks store information by making short-term alterations to the synapses. The study sheds new light on short-term synaptic plasticity in recent memory storage.

Source: picower institute for learning and memory.

Between the time you read the Wi-Fi password off the café’s menu board and the time you can get back to your laptop to enter it, you have to hold it in mind. If you’ve ever wondered how your brain does that, you are asking a question about working memory that has researchers have strived for decades to explain. Now MIT neuroscientists have published a key new insight to explain how it works.

Code-generating AI can introduce security vulnerabilities, study finds

A recent study finds that software engineers who use code-generating AI systems are more likely to cause security vulnerabilities in the apps they develop. The paper, co-authored by a team of researchers affiliated with Stanford, highlights the potential pitfalls of code-generating systems as vendors like GitHub start marketing them in earnest.

“Code-generating systems are currently not a replacement for human developers,” Neil Perry, a PhD candidate at Stanford and the lead co-author on the study, told TechCrunch in an email interview. “Developers using them to complete tasks outside of their own areas of expertise should be concerned, and those using them to speed up tasks that they are already skilled at should carefully double-check the outputs and the context that they are used in in the overall project.”

The Stanford study looked specifically at Codex, the AI code-generating system developed by San Francisco-based research lab OpenAI. (Codex powers Copilot.) The researchers recruited 47 developers — ranging from undergraduate students to industry professionals with decades of programming experience — to use Codex to complete security-related problems across programming languages including Python, JavaScript and C.

The Brief History of Artificial Intelligence: The World Has Changed Fast—What Might Be Next?

Cotra’s work is particularly relevant in this context as she based her forecast on the kind of historical long-run trend of training computation that we just studied. But it is worth noting that other forecasters who rely on different considerations arrive at broadly similar conclusions. As I show in my article on AI timelines, many AI experts believe that there is a real chance that human-level artificial intelligence will be developed within the next decades, and some believe that it will exist much sooner.

Building a Public Resource to Enable the Necessary Public Conversation

Computers and artificial intelligence have changed our world immensely, but we are still at the early stages of this history. Because this technology feels so familiar, it is easy to forget that all of these technologies that we interact with are very recent innovations, and that most profound changes are yet to come.

What to expect from AI in 2023

As a rather commercially successful author once wrote, “the night is dark and full of terrors, the day bright and beautiful and full of hope.” It’s fitting imagery for AI, which like all tech has its upsides and downsides.

Art-generating models like Stable Diffusion, for instance, have led to incredible outpourings of creativity, powering apps and even entirely new business models. On the other hand, its open source nature lets bad actors use it to create deepfakes at scale — all while artists protest that it’s profiting off of their work.

What’s on deck for AI in 2023? Will regulation rein in the worst of what AI brings, or are the floodgates open? Will powerful, transformative new forms of AI emerge, à la ChatGPT, disrupting industries once thought safe from automation?

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