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Category: robotics/AI – Page 1,366

An AI can decode speech from brain activity with surprising accuracy

The research is still a ways away from helping people who can’t communicate through speech.

An artificial intelligence can decode words and sentences from brain activity with surprising — but still limited — accuracy. Using only a few seconds of brain activity data, the AI guesses what a person has heard. It lists the correct answer in its top 10 possibilities up to 73 percent of the time, researchers found in a preliminary study.

The AI’s “performance was above what many people thought was possible at this stage,” says Giovanni Di Liberto, a computer scientist at Trinity College Dublin who was not involved in the research.

Developed by Facebook’s parent company, Meta, the AI could eventually be used to help people who can’t communicate through speech, typing or gestures.

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China: AI-powered humanoid robot named CEO of company

Tang Yu will help in enabling a more effective risk management system.

A Chinese metaverse company has appointed a robot as its CEO! Yes, you read it right. It may sound straight out of a Sci-Fi movie but it is true. Chinese company, NetDragon Websoft develops and operates multiplayer online games and also makes mobile applications.

Recently, the Chinese gaming company announced the appointment of its new CEO ‘Ms. Tang Yu’. And…the CEO is an AI-powered virtual humanoid robot. Tang Yu has been appointed as the CEO of the company’s principal subsidiary, Fujian NetDragon Websoft. It has become the world’s first robot to hold an executive position.

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How AI content generators work

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Artificial intelligence (AI) has been steadily influencing business processes, automating repetitive and mundane tasks even for complex industries like construction and medicine.

While AI applications often work beneath the surface, AI-based content generators are front and center as businesses try to keep up with the increased demand for original content. However, creating content takes time, and producing high-quality material regularly can be difficult. For that reason, AI continues to find its way into creative business processes like content marketing to alleviate such problems.

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Amazon acquires warehouse machinery and robotics maker Cloostermans

Cloostermans will become part of Amazon Robotics, Amazon’s division focused on automating aspects of its warehouse operations. The unit was formed after Amazon acquired Kiva Systems, a manufacturer of warehouse robots, for $775 million a decade ago.

Amazon continues to launch new machines in warehouses. In June, the company unveiled a package ferrying machine called Proteus, which it referred to as its first fully autonomous mobile robot. It’s also deployed other robots that can help sort and move packages.

In a blog post, Ian Simpson, vice president of Global Robotics at Amazon, said the company is investing in robotics and other technology to make its warehouses safer for employees.

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Do I sound ill? — All About Vocal Biomarkers Diagnosing Illnesses

Vocal biomarkers have become a buzzword during the pandemic, but what does it mean and how could it contribute to diagnostics?

What if a disease could be identified over a phone call?

Vocal biomarkers have amazing potential in reforming diagnostics. As certain diseases, like those affecting the heart, lungs, vocal folds or the brain can alter a person’s voice, artificial intelligence (A.I.)-based voice analyses provide new horizons in medicine.

Using biomarkers for diagnosis and remote monitoring can also be used for COVID-screening. So is it possible to diagnose illnesses from the sound of your voice?

Vocal biomarkers give us new opportunities in prevention also.

Let’s have a look at where this technology stands today.

Continue reading “Do I sound ill? — All About Vocal Biomarkers Diagnosing Illnesses” | >

Automatically optimizing execution of unfamiliar tensor operations

At this year’s Conference on Machine Learning and Systems (MLSys), we and our colleagues presented a new auto-scheduler called DietCode, which handles dynamic-shape workloads much more efficiently than its predecessors. Where existing auto-encoders have to optimize each possible shape individually, DietCode constructs a shape-generic search space that enables it to optimize all possible shapes simultaneously.

We tested our approach on a natural-language-processing (NLP) task that could take inputs ranging in size from 1 to 128 tokens. When we use a random sampling of input sizes that reflects a plausible real-world distribution, we speed up the optimization process almost sixfold relative to the best prior auto-scheduler. That speedup increases to more than 94-fold when we consider all possible shapes.

Despite being much faster, DietCode also improves the performance of the resulting code, by up to 70% relative to prior auto-schedulers and up to 19% relative to hand-optimized code in existing tensor operation libraries. It thus promises to speed up our customers’ dynamic-shaped machine learning workloads.

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With Stable Diffusion, you may never believe what you see online again

AI image generation is here in a big way. A newly released open source image synthesis model called Stable Diffusion allows anyone with a PC and a decent GPU to conjure up almost any visual reality they can imagine. It can imitate virtually any visual style, and if you feed it a descriptive phrase, the results appear on your screen like magic.

Some artists are delighted by the prospect, others aren’t happy about it, and society at large still seems largely unaware of the rapidly evolving tech revolution taking place through communities on Twitter, Discord, and Github. Image synthesis arguably brings implications as big as the invention of the camera—or perhaps the creation of visual art itself. Even our sense of history might be at stake, depending on how things shake out. Either way, Stable Diffusion is leading a new wave of deep learning creative tools that are poised to revolutionize the creation of visual media.

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Training cost for Stable Diffusion was just $600,000 and that is a good sign for AI progress

Stable Diffusion is a powerful open-source image AI that competes with OpenAI’s DALL-E 2. The AI training was probably rather cheap in comparison.

Anyone interested can download the model of the open-source image AI Stable Diffusion for free from Github and run it locally on a compatible graphics card. This must be reasonably powerful (at least 5.1 GB VRAM), but you don’t need a high-end computer.

In addition to the local, free version, the Stable Diffusion team also offers access via a web interface. For about $12, you get roughly 1,000 image prompts.

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