Lifeboat Foundation

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.

Continue reading “The Unexpected Winners Of The ChatGPT Generative AI Revolution” »

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.

Welcome to The Interchange ! If you received this in your inbox, thank you for signing up and your vote of confidence. If you’re reading this as a post on our site, sign up here so you can receive it directly in the future. Every week, I’ll take a look at the hottest fintech news of the previous week. This will include everything from funding rounds to trends to an analysis of a particular space to hot takes on a particular company or phenomenon. There’s a lot of fintech news out there and it’s my job to stay on top of it — and make sense of it — so you can stay in the know. — Mary Ann

Storied venture firms Sequoia Capital and Andreessen Horowitz (a16z) invested more in fintech than any other category in 2022, according to research from CB Insights. I’m not going to lie — upon learning this, my fintech-loving ears perked up.

Sequoia apparently was fairly active overall last year despite the global downturn, with over 100 investments. And fintech represented nearly a quarter of the firm’s deals.

Law-makers must act like speculative fiction authors and try to foresee how technology will change our world, says writer Ray Nayler.

The congealed mat of yeast and bacteria cells that forms on top of the brewed drink kombucha could be used to make light, cheap and flexible circuit boards for wearable electronics or even partially living rudimentary computers.

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.

The US Department of Energy has assessed that the Covid-19 pandemic most likely came from a laboratory leak in China, according to a newly updated classified intelligence report.

Two sources said that the Department of Energy assessed in the intelligence report that it had “low confidence” the Covid-19 virus accidentally escaped from a lab in Wuhan.

Intelligence agencies can make assessments with either low, medium or high confidence. A low confidence assessment generally means that the information obtained is not reliable enough or too fragmented to make a more definitive analytic judgment or that there is not enough information available to draw a more robust conclusion.

Electronic devices generate heat, and that heat must be dissipated. If it isn’t, the high temperatures can compromise device function, or even damage the devices and their surroundings.

Now, a team from UIUC and UC Berkeley have published a paper in Nature Electronics detailing a new cooling method that offers a host of benefits, not the least of which is space efficiency that offers a substantial increase over conventional approaches in devices’ power per unit volume.

Tarek Gebrael, the lead author and a PhD student in mechanical engineering, explains that the existing solutions suffer from three shortcomings. “First, they can be expensive and difficult to scale up,” he says. Heat spreaders made of diamond, for example, are sometimes used at the chip level, but they aren’t cheap.