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Category: robotics/AI – Page 636

The biggest companies in AI aren’t interested in paying to use copyrighted material as training data, and here are their reasons why.

The US Copyright Office is taking public comment on potential new rules around generative AI’s use of copyrighted materials, and the biggest AI companies in the world had plenty to say. We’ve collected the arguments from Meta, Google, Microsoft, Adobe, Hugging Face, StabilityAI, and Anthropic below, as well as a response from Apple that focused on copyrighting AI-written code.

There are some differences in their approaches, but the overall message for most is the same: They don’t think they should have to pay to train AI models on copyrighted work.

The Copyright… More

Continue reading “AI companies have all kinds of arguments against paying for copyrighted content” | >

‘Prompt injection’ attacks haven’t caused giant problems yet. But it’s a matter of time, researchers say.

Imagine a chatbot is applying for a job as your personal assistant. The pros: This chatbot is powered by a cutting-edge large language model. It can write your emails, search your files, summarize websites and converse with you.

The con: It will take orders from absolutely anyone.

AI chatbots are good at many things, but they struggle to tell the difference between legitimate commands from their users and manipulative commands from outsiders. It’s an AI Achilles’ heel, cybersecurity researchers say, and it’s a matter of time before attackers take advantage of it.

Continue reading “Chatbots are so gullible, they’ll take directions from hackers” | >

Scientists showcased the application of machine learning in the sodium-cooled fast reactor (SFR).

Machine learning technology has the potential to transform nuclear reactor operations, according to a team of experts from the US Department of Energy’s Argonne National Laboratory, who demonstrated how it may improve security and efficiency.

They showcased the application of machine learning in the sodium-cooled fast reactor (SFR), a specialized cutting-edge nuclear reactor.

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Hackers are using WormGPT, a rogue AI tool, to write phishing emails and malware.

Cybersecurity experts have warned that a new generative AI tool called WormGPT, which is being sold on the dark web, poses a serious threat to businesses and individuals.

IStock/BrianAJackson.

What is WormGPT?

Continue reading “WormGPT: Dark web’s new AI weapon for cyberattacks” | >

Link :- Will AI be the source of new employment or the end of more traditional roles? A new study seeks to answer this one crucial question.

Demaerre/iStock.

AI-powered automation has the ability to take over routine, repetitive, and manual processes. Consequently, employment in sectors such as manufacturing, data entry and customer service may be vulnerable with workers in these industries losing their jobs.

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Leaks show that OpenAI will be unveiling major updates to ChatGPT at its developer conference on 6 November. These include custom chatbots, a business subscription, and connections to Google and Microsoft.

OpenAI’s first-ever developer conference will take place on the 6th of November, where the company plans to unveil a number of updates. Leaks now show that these will include a new interface for ChatGPT as well as completely new features.

OpenAI introduces custom chatbots via Gizmo.

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With “Grok”, Elon Musk introduces a chatbot built with “X” data for “X” premium users. In contrast to OpenAI with ChatGPT, Musk gives the chatbot more creative leeway in its responses.

Musk and his company describe Grok as a humorous, witty, and rebellious chatbot that can answer almost any question. Grok uses its model knowledge based on Internet and X data, as well as real-time information from X, to provide answers. According to xAI, the chatbot also answers “spicy questions” that would be rejected by most other AI systems.

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Researchers present RoboGen, a generative robotic agent that automatically learns new skills in a generative simulation.

The work by researchers from CMU, Tsinghua IIIS, MIT CSAIL, UMass Amherst, and the MIT-IBM AI Lab aims to leverage recent advances in generative AI to generate infinite training data for automated robot learning.

According to the team, RoboGen is a generative robotic agent that learns various robotic tasks automatically and en masse through generative simulation. The team is using existing foundation models, such as OpenAI’s GPT-4, to “automatically generate diversified tasks, scenes, and training supervisions, thereby scaling up robotic skill learning with minimal human supervision.”

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Imagine you’re visiting a friend abroad, and you look inside their fridge to see what would make for a great breakfast. Many of the items initially appear foreign to you, with each one encased in unfamiliar packaging and containers. Despite these visual distinctions, you begin to understand what each one is used for and pick them up as needed.

Inspired by humans’ ability to handle unfamiliar objects, a group from MIT’s Computer Science and Artificial Intelligence Laboratory (CSAIL) designed Feature Fields for Robotic Manipulation (F3RM), a system that blends 2D images with foundation model features into 3D scenes to help robots identify and grasp nearby items. F3RM can interpret open-ended language prompts from humans, making the method helpful in real-world environments that contain thousands of objects, like warehouses and households.

F3RM offers robots the ability to interpret open-ended text prompts using natural language, helping the machines manipulate objects. As a result, the machines can understand less-specific requests from humans and still complete the desired task. For example, if a user asks the robot to “pick up a tall mug,” the robot can locate and grab the item that best fits that description.

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