Zach Kirkhorn’s replacement, Delhi-trained accountant Vaibhav Taneja, has kept a low profile since joining Tesla in 2016—a very low profile.
When an artist – whether they are a painter, writer, photographer, poet, etc. – creates a piece of work, they automatically own the copyright to it. This means they get to choose how that work of art can be used and, of course, get paid for it. But what happens when a piece of art is created by a computer?
This is a problem that we’ve only had to deal with in the last year – since Generative AI took the world by storm. Tools like ChatGPT can write stories, songs or plays, while Stable Diffusion or DALL-E 2 can produce images of anything we can describe to them.
But should the credit (and royalties) go to the person who used the tool to create the art or to the company that built the AI tool?… More.
Continue reading “Is Generative AI Stealing From Artists?” »
The regulatory chairman told Dealbook that people piling into the most dominant AI models will raise risks for a crash.
Another day, another step closer to the normalization of build-your-own AI chatbot partners.
Per Decrypt, top-shelf Silicon Valley VC firm Andreessen Horowitz last week took to the developer site GitHub to lay out detailed instructions on how to build an AI companion bot from scratch. The VC outfit has a lot of money in various AI ventures, the billion-dollar AI companion startup Character. AI included; now, it seems that the folks at the firm are so enthusiastic about companion bots that they’re encouraging curious developers out there to start DIYing versions for themselves — and among several other potential use cases, it feels notable that romantic partnership was listed as use case number one.
“There are many possible use cases for these companions — romantic (AI girlfriends / boyfriends), friendship, entertainment, coaching, etc,” reads the description, noting elsewhere that the “project is purely intended to be a developer tutorial and starter stack for those curious on how chatbots are built.”
MySpace gave us co-founder Tom right off the bat: join the social network and you started with at least one friend, even if he never interacted with you. Now social platforms like Snapchat and Facebook are using generative artificial intelligence to give us smarter and more engaging friends.
When Facebook parent company Meta reported financial results last week, CEO Mark Zuckerberg said he saw the AI friend as an assistant or coach that “can help you interact with businesses.” Facebook’s AI chatbots will reportedly offer a range of personalities and capabilities, presumably in the hope that at least one will appeal to most if not all Facebook users.
According to Financial Times reporting, Zuckerberg is “spending all his energy and time” on this: a massive shift from the metaverse and virtual reality, his previous idée fixe.
Despite that drop, the company did better than expected. Wall Street had forecast it would lose 3 cents a share on an adjusted basis on sales of $12.1 billion, according to Yahoo Finance.
“Our overall position is strengthening,” CEO Pat Gelsinger told analysts, adding later, “simply put, it was a very good quarter.”
Still, he and Chief Financial Officer Dave Zinsner noted that the selling environment was improving only slowly, particularly for server chips.
By simply pressing the tab key, a developer using Copilot can finish a line, generate blocks of code, or even write entire programs. According to GitHub, over 10,000 organizations, ranging from Coca-Cola to Airbnb, have signed up for Copilot’s enterprise version, and more than 30,000 employees at Microsoft itself now regularly code with assistance from Copilot.
“Sooner than later, 80% of the code is going to be written by Copilot. And that doesn’t mean the developer is going to be replaced.”
Recently, Freethink spoke with Thomas Dohmke, GitHub’s CEO, to learn more about how Copilot promises to refashion programming as a profession, and the questions AI-powered development raises about the future of innovation itself. We also talked about why coding with Copilot is so much fun, how AI is going to change the way we learn, and whether Copilot can fix banks that are still running COBOL on mainframes.
British health tech startup Twinn Health recently emerged from stealth, boasting an AI-powered platform that analyzes MRI scans to detect preventable disease “earlier than ever before.” Starting with metabolic disease, the company’s AI platform leverages validated imaging biomarkers to improve diagnosis and treatment decisions.
With age-related frailty and liver disease also on its roadmap, Twinn Health is positioning itself squarely in the domain of longevity and preventive healthcare. The company is supported by WAED, a $500 million venture capital fund backed by Saudi Aramco, which invests in innovative tech-based startups.
Longevity. Technology: Magnetic resonance imaging (MRI) has been used in healthcare for decades and is widely used in hospitals and clinics for the diagnosis and follow-up of disease. In recent years, AI tools have appeared that help identify the presence of specific conditions within MRI scans, but the technology is not yet widely used in healthcare to support healthspan and longevity improvements. Twinn Health aims to change that, combining MRI and AI to enable the early detection and management of multiple age-related diseases. To learn more, we caught up with founder and CEO Dr Wareed Alenaini.
Summary: Religious groups may find their credibility and financial support undermined with the growing use of AI and robot preachers, according to researchers.
The study involved experiments with the Mindar humanoid robot in Japan and Pepper in Singapore, both delivering sermons to audiences. Participants rated these robotic preachers as less credible than their human counterparts, contributing to decreased donations.
Despite some acceptance, the study highlights the importance of human connection and credibility in religious leadership.
Cybersecurity researchers said they have discovered what they say is the first open-source software supply chain attacks specifically targeting the banking sector.
“These attacks showcased advanced techniques, including targeting specific components in web assets of the victim bank by attaching malicious functionalities to it,” Checkmarx said in a report published last week.
“The attackers employed deceptive tactics such as creating a fake LinkedIn profile to appear credible and customized command-and-control (C2) centers for each target, exploiting legitimate services for illicit activities.”
