The New York Times is suing OpenAI and its close collaborator (and investor), Microsoft, for allegedly violating copyright law by training generative AI models on Times’ content.
Actress Sarah Silverman joined a pair of lawsuits in July that accuse Meta and OpenAI of having “ingested” Silverman’s memoir to train their AI models.
As The Times’ complaint alludes to, generative AI models have a tendency to regurgitate training data, for example reproducing almost verbatim results from articles.
And that’s why most [lawsuits like this] will probably fail.”Some news outlets, rather than fight generative AI vendors in court, have chosen to ink licensing agreements with them.
In its complaint, The Times says that it attempted to reach a licensing arrangement with Microsoft and OpenAI in April but that talks weren’t ultimately fruitful.
According to DocSend data, investors aren’t scouring pitch decks as earnestly as they were in the past.
“For founders now, perfecting the pitch, having an efficient sales strategy, and scoping the product with urgency will create a strong foundation for success that attracts investors.”Thanks for reading and happy holidays!
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“The drier funding climate of 2023 only served to weed out the weaker businesses that had managed to secure capital in 2021,” she writes.
Application programming interfaces (APIs) power the modern internet, including most websites, mobile apps, and IoT devices we use.
This phenomenon, often referred to as the “API economy,” is projected to have a total market value of $14.2 trillion by 2027.
How AI integration changed the API landscapeVarious kinds of AI have been here for a while, but it’s generative AI (and LLMs) that completely changed the risk landscape.
Many AI companies use the benefits of API technologies to bring their products to every home and workplace.
Various kinds of AI have been here for a while, but it’s generative AI (and large language models [LLMs]) that completely changed the risk landscape.
Arkon Energy, a data center infrastructure company, closed a $110 million private funding round to expand its operations, the company’s CEO Josh Payne shared exclusively with TechCrunch.
“These sites appeal to both bitcoin miners and AI [or] machine learning clients who have very high power computing demands,” Payne said.
“We are essentially a landlord who owns the underlying infrastructure assets.”Arkon’s business model focuses on strategically acquiring distressed data center assets across the globe.
“The current and future demand for data center capacity of all types that we are seeing globally, but especially in the U.S., is unprecedented and monumental.
Arkon aims to fill that gap by providing the underlying infrastructure layer that the AI sector relies on.
Akron Energy, a data center infrastructure company, closed a $110 million private funding round to expand its operations, the company’s CEO Josh Payne shared exclusively with TechCrunch.
“These sites appeal to both bitcoin miners and AI [or] machine learning clients who have very high power computing demands,” Payne said.
“We are essentially a landlord who owns the underlying infrastructure assets.”Akron’s business model focuses on strategically acquiring distressed data center assets across the globe.
“The current and future demand for data center capacity of all types that we are seeing globally, but especially in the U.S., is unprecedented and monumental.
Akron aims to fill that gap by providing the underlying infrastructure layer that the AI sector relies on.
Working to apply artificial intelligence to molecular simulations, DP, short for “Deep Potential”, believes that the unifying power of “scientific research for humanity” will pave the way for its global expansion.
Areas that can benefit from scientific computing range from biopharmaceutical research and car design to semiconductor development.
The London-based AI powerhouse reported £44 million ($60 million) profit in 2020, up from a whopping £477 million ($650 million) loss in 2019.
In the meantime, DP’s international ambitions might encounter roadblocks from the ongoing decoupling that’s dividing the U.S. and China across many areas, including scientific research.
“Both the fields of basic science and biopharmaceuticals are shared by all of humanity, and they are relatively open and inclusive.
Ask Sophie: Is it easier yet for AI founders to get green cards?
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How is the administration making it easier for AI companies to sponsor employees for permanent residence?
Will the number of green cards earmarked for individuals in the AI field increase?
Even though the economy is signaling a bit of a bounce-back, 2024 might not be much better than 2023 when it comes to startups sharing a piece of the budget pie.
If startups want a chance of making it through yet another bumpy year, they need to prove their worth now more than ever.
Investors told TechCrunch’s Ron Miller and Rebecca Szkutak that they’re still expecting some pockets of growth.
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For example, 70% of respondents said they plan to hire next year and none are looking to downsize.
Microsoft Copilot, Microsoft’s AI-powered chatbot, can now compose songs thanks to an integration with gen AI music app Suno.
From a single sentence, Suno can generate complete songs — including lyrics, instrumentals and singing voices.
Meta has published several of its experiments with AI music generation.
Stability AI’s own gen AI audio lead quit after saying that gen AI “exploits creators,” and the Grammys have banned fully AI-generated song from consideration for awards.
Clarity on the legal status of gen AI music may arrive soon — if not from court decisions.
The plan is for “centers of excellence” to be set up to support the development of dedicated AI algorithms that can run on the EU’s supercomputers, they added.
AI startups are more likely to be accustomed to using dedicated compute hardware provided by US hyperscalers to train their models than tapping the processing power offered by supercomputers as a training resource.
Using its supercomputing resources to fire up AI startups specifically has emerged as a more recent strategic priority after the EU president’s announcement of the compute access for AI model training program this fall.
It’s still early days for the EU’s ‘supercompute for AI’ program so it’s unclear whether there’s much model training upside to report off of dedicated access as yet.
But the early presence of Mistral in the EU’s supercomputing access program may suggest an alignment in the thinking.
