The Fundamental AI Research (FAIR) team at Meta, Facebook’s parent company, has introduced a new “state-of-the-art” artificial intelligence (AI) language model called Large Language Model Meta AI (LLaMA).
The model will be made accessible to researchers, and is anticipated to aid scientists and engineers as they investigate new uses of AI, CEO Mark Zuckerberg announced on Friday.
Over half of the studied companies in the United States have deployed OpenAI’s ChatGPT chatbot, according to a recent study.
And nearly half of these businesses disclosed that ChatGPT had already replaced a number of their employees, claimed the survey done by Resumebuilder.com, involving 1,000 business leaders.
This new technology is still in its early stages in the workplace, “workers need to surely be thinking of how it may affect the responsibilities of their current job,” said Stacie Haller, Chief Career Advisor at Resumebuilder.com.
Costing tens of thousands of dollars, these robots were clearing tables and keeping cafeterias clean.
If human workers have been complaining about robots taking over their jobs, the macroeconomic situation has now put robots out of work.
Over a hundred robots at Google’s parent company, Alphabet, have allegedly been fired after the team maintaining them was shut down, Wired reported.
After a dip in advertisement revenues last year, Google’s Alphabet is preparing for the worse by firing expensive robots. Over a hundred robots have already been fired after the team maintaining them was shut down.
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The chipmaker reported an adjusted EPS of $0.88, which was better than the analyst consensus prediction of $0.81. In addition, Nvidia’s Q4 revenue came out to $6.05 billion, which was better than the expected $6.0 billion.
Alongside these numbers came a renewed commitment to its cloud AI endeavors, which has analysts and investors buzzing. Here, we’ll cover what you need to know if you’re considering investing in Nvidia.
ChatGPT has taken the tech world by storm, showcasing artificial intelligence (AI) with conversational abilities that go far beyond anything we’ve seen before. The viral chatbot interface is based on GPT-3, said to be one of the largest and most complex language models ever created — trained on 175 billion “parameters” (data points).
However, it’s something of an open secret that its creator — the AI research organization OpenAI — is well into development of its successor, GPT-4. Rumor has it that GPT-4 will be far more powerful and capable than GPT-3.
GPT-3 is the AI model underpinning the super-popular AI tool ChatGPT. OpenAI, the creator of GPT-3, is working on developing the next version of their model (GPT-4). Here we explore the many rumors and speculations.
OpenAI’s ChatGPT has taken the world like wildfire and continues to make headlines. However, the Generative Artificial Intelligence (GAI) has been around for a very long time. The technology was first pioneered in academia with Ian Goodfellow and Yoshua Bengio publishing their first seminal work on Generative Adversarial Networks in 2014 and then Google picked up the torch and published seminal papers and patents in both GANs and generative pre-trained transformers (GPT). In fact, my first paper on generative chemistry, was published in 2016, first granted patent in 2018, and the first AI-generated drug went through the first phase of clinical trials.
Forbes is one of the most reputable content providers on the planet and probably the most reputable when it comes to anything dealing with money. If Forbes does not classify you as a billionaire, you are not a billionaire. It has decades of high-quality expert-generated longitudinal text, and multimedia content in multiple languages. In addition to elite human reporters and editors, it also has a small army of content creators specializing in specific areas contributing to Forbes.com. For example, it is my 5th year as a contributor and I contribute regularly to keep the pencil sharp. This massive human intelligence may be partly repurposed to help develop internal generative resources within the Forbes empire, help curate the datasets and help train or benchmark third-party generative resources. I would gladly volunteer a small amount of time to such a task.
Nature and several other journals in the Nature Publishing Group portfolio are considered to be the Olympus in academic publishing. To publish in one of the elite Nature journals academics spend months and sometimes years going through the rounds of editorial and then peer-review. The quality of the data is questioned, all experimental data is disclosed, and the thousands or millions of dollars that went into the experiments are presented in the form of a paper and supplementary materials.
Having vast amounts of highest-quality data that is not available to the public gives Nature and other publishers the ability to either develop their own versions of ChatGPT, sell or license the data, and restructure the editorial and review processes to create more value for the future generative systems.
On stage in front of packed rooms, at lavish private venture capital dinners and over casual games of ping pong, San Francisco’s AI startup scene is blowing up. With tens of thousands of laid off software engineers with time to tinker, glistening empty buildings beckoning them to start something new, and billions of dollars in idle cash in need of investing, it’s no surprise that just weeks after viral AI companion ChatGPT made its jaw-dropping debut on Nov. 30, one of the smartest cities in the world would pick generative AI as the driver of its next economic boom.
San Francisco’s AI startup scene is blowing up thanks to the ChatGPT craze and backing from investors like Y Combinator, Bessemer, Coatue, Andreessen Horowitz, Tiger Global, Mark Benioff’s Time Ventures and Ashton Kutcher’s Sound Ventures. Meet the players who are shaking up the tech mecca.
When Microsoft released Bing Chat, an AI-powered chatbot co-developed with OpenAI, it didn’t take long before users found creative ways to break it. Using carefully tailored inputs, users were able to get it to profess love, threaten harm, defend the Holocaust and invent conspiracy theories. Can AI ever be protected from these malicious prompts?
What set it off is malicious prompt engineering, or when an AI, like Bing Chat, that uses text-based instructions — prompts — to accomplish tasks is tricked by malicious, adversarial prompts (e.g. to perform tasks that weren’t a part of its objective. Bing Chat wasn’t designed with the intention of writing neo-Nazi propaganda. But because it was trained on vast amounts of text from the internet — some of it toxic — it’s susceptible to falling into unfortunate patterns.
Adam Hyland, a Ph.D. student at the University of Washington’s Human Centered Design and Engineering program, compared prompt engineering to an escalation of privilege attack. With escalation of privilege, a hacker is able to access resources — memory, for example — normally restricted to them because an audit didn’t capture all possible exploits.
On December 18, 2019, Wuhan Central Hospital admitted a patient with symptoms common for the winter flu season: a 65-year-old man with fever and pneumonia. AI Fen, director of the emergency department, oversaw a typical treatment plan, including antibiotics and anti-influenza drugs.
Six days later, the patient was still sick, and AI was puzzled, according to news reports and a detailed reconstruction of this period by evolutionary biologist Michael Worobey. The respiratory department decided to try to identify the guilty pathogen by reading its genetic code, a process called sequencing. They rinsed part of the patient’s lungs with saline, collected the liquid, and sent the sample to a biotech company. On December 27, the hospital got the results: The man had contracted a new coronavirus closely related to the one that caused the SARS outbreak that began 17 years before.
This time lapse of a neural network with the neurons slowly switching off is a haunting experiment in machine learning.
