Powered by OpenAI technology, the A.I. version of a popular Snapchat influencer is made over $70,000 in a week, marking the beginning of an ethically-thorny era.
So you are pretty sure artificial intelligence is the future and you want a job in AI before it takes yours, but you don’t know how to code or have a background in technology. Not to worry! There’s a new job you are likely qualified for, and it’s paying hundreds of thousands of dollars a year.
What To Know: Microsoft Corp MSFT-backed ChatGPT has taken the world by storm. It exceeded 100 million monthly active users in two months’ time, making it the fastest-growing platform ever, and it’s not slowing down.
The thing about chatbots like ChatGPT is they need to be taught by humans. After a developer builds a large language model (LLM), the program needs to learn to communicate. That’s where you could come into play.
At its I/O developer conference, the search giant needs to rethink its AI strategy if it wants to catch Microsoft. The missing element? Experimentation.
Google has had a rough six months. Since ChatGPT launched last November — followed by the new Bing in February and GPT-4 in March — the company has failed to establish its AI credentials. Its own offering, the “experimental” chatbot Bard, compares poorly to rivals, and insider reports have portrayed a company in panic and disarray. Today, at its annual I/O conference, the company needs to convince the public (and shareholders) that it has a meaningful response. But to do that, it needs a new playbook.
AI outputs are increasingly defining the cultural moment — just not Google’s.
Continue reading “Google needs to stop throwing good money after Bard” »
The demo is clever, questionably real, and prompts a lot of questions about how this device will actually work.
Buzz has been building around the secretive tech startup Humane for over a year, and now the company is finally offering a look at what it’s been building. At TED last month, Humane co-founder Imran Chaudhri gave a demonstration of the AI-powered wearable the company is building as a replacement for smartphones. Bits of the video leaked online after the event, but the full video is now available to watch.
The device appears to be a small black puck that slips into your breast pocket, with a camera, projector, and speaker sticking out the top.
Continue reading “Humane’s new wearable AI demo is wild to watch — and we have lots of questions” »
Mandopop singer Stefanie Sun has gone viral on Bilibili, China’s largest user-generated video streaming site. But the sudden revival of interest in Sun, who hasn’t released an album since 2017, comes not from the artist having another moment of genius.
The songs that have attracted millions of views on Bilibili feature Sun’s voice cloned by artificial intelligence, raising questions about copyright protection.
Reminiscing on the golden age of Mandarin pop music, tech-savvy Chinese internet users took the liberty of mimicking Sun’s voice using singing voice conversion, a deep learning method that lets a user deliver one person’s singing in another person’s voice, and swap it into a compilation of Mandpop classics.
An innovative method decodes and finds hidden relationships in jointly recorded neural and behavioural data.
Amid all the hype and hysteria about ChatGPT, Bard, and other generative large language models (LLMs), it’s worth taking a step back to look at the gamut of AI algorithms and their uses. After all, many “traditional” machine learning algorithms have been solving important problems for decades—and they’re still going strong. Why should LLMs get all the attention?
Before we dive in, recall that machine learning is a class of methods for automatically creating predictive models from data. Machine learning algorithms are the engines of machine learning, meaning it is the algorithms that turn a data set into a model. Which kind of algorithm works best (supervised, unsupervised, classification, regression, etc.) depends on the kind of problem you’re solving, the computing resources available, and the nature of the data.
In the next section, I’ll briefly survey the different kinds of machine learning and the different kinds of machine learning models. Then I’ll discuss 14 of the most commonly used machine learning and deep learning algorithms, and explain how those algorithms relate to the creation of models for prediction, classification, image processing, language processing, game-playing and robotics, and generative AI.
TerraPower, founded by billionaire and Microsoft co-founder Bill Gates in 2008, is opening a new nuclear power plant in Kemmerer, Wyoming. The plant will be the first of its kind, with the company hoping to revolutionize the nuclear energy industry in the U.S. to help fight climate change and support American energy independence.
“Nuclear energy, if we do it right, will help us solve our climate goals,” Gates told ABC News. “That is, get rid of the greenhouse gas emissions without making the electricity system far more expensive or less reliable.”
Gates met with ABC News’ chief business, economics, and technology correspondent Rebecca Jarvis in Kemmerer to talk about the project.
Shap-E is a model that allows you to generate 3D objects from text, building off OpenAI’s other AI tools.
The Work Trend Index report found that leaders believe analytical judgment, flexibility and emotional intelligence are essential skills for the future of work.
