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Enhancing Business Efficiency: Leap AI streamlines AI workflow integration

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Leap AI is building a solution for these companies to easily integrate AI-powered workflows or even build their own using an easy process. It also has plans starting from $29 per month with more credits, no limit on building workflows with customer support. Why did the founders build Leap AI? Another unique aspect is that we provide the interoperability between multiple models, multiple vendors, and multiple companies,” he said. Leap AI is also working on improving context awareness of its workflows so it can leverage previously generated results.

“Revolutionize the Music Industry on-the-go with Will.i.am’s Latest Venture, Sound Drive”

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The new venture will launch this summer in Mercedes-Benz’s electric EQ models, will.i.am told TechCrunch during a press event. That car had 16 Sound Drive tracks loaded, some familiar and others created especially for the experience. Sound Drive is not quite a performance as such, Will.i.am likens being a conductor or DJ, but that’s just the beginning. Down the road, Sound Drive will let you geotag samples, linking auditory cues with memories. Mercedes-Benz is the first partner, where the technology will launch with 10 tracks this summer as MBUX Sound Drive.

“Reviving the Popularity of Venture Debt: Arc’s Mission”

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Venture debt has its merits. That’s why it’s interesting that startup finance company Arc Technologies is choosing now to take on the $30 billion venture debt industry with a venture debt marketplace for Silicon Valley. There’s a larger pool of debt capital that’s now available to these companies because they’re stronger and more resilient. That’s what Arc is solving with its Arc Capital Markets debt marketplace. “We want to help founders and CFOs weather the ongoing storm in the venture capital funding route and ensure that they’re continuing to grow efficiently with minimal dilution.”

“Enhance Your PC Experience with Microsoft’s New Copilot Key”

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Microsoft would like 2024 to be the “year of the AI PC” and to put a point on that, the company today announced a new key for Copilot — that is, a physical key that will soon make its way to your keyboard and join the Windows key, together with its friends the Control key, Alt and that Insert key you’ve never purposely used. Based on the image Microsoft sent over, it looks like the new Copilot key will replace the right Control key on the standard PC keyboard, where it will slot in between the Alt key and the left arrow key. “The introduction of the Copilot key marks the first significant change to the Windows PC keyboard in nearly three decades,” Microsoft’s Yusuf Mehdi, Executive Vice President & Consumer Chief Marketing Officer, writes in today’s announcement. The Copilot key joins the Windows key as a core part of the PC keyboard and when pressed, the new key will invoke the Copilot in Windows experience to make it seamless to engage Copilot in your day to day.”In regions where Copilot is not available, the Copilot key will launch Windows Search. The first keyboards with the new key will launch at this year’s CES in Las Vegas and will likely start shipping in late February.

Assisting Businesses with Offline Deployment of LLMs: Giga ML’s Solution

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In search of one, they founded Giga ML, a startup building a platform that lets companies deploy LLMs on-premise — ostensibly cutting costs and preserving privacy in the process. “Giga ML addresses both of these challenges.”Giga ML offers its own set of LLMs, the “X1 series,” for tasks like generating code and answering common customer questions (e.g. But it’s tough to say how X1 compares qualitatively; this reporter tried Giga ML’s online demo but ran into technical issues. Even if Giga ML’s models are superior in some aspects, though, can they really make a splash in the ocean of open source, offline LLMs? “Giga ML’s mission is to help enterprises safely and efficiently deploy LLMs on their own on-premises infrastructure or virtual private cloud,” Vummadi said.

“OpenAI and Microsoft Called Upon by The New York Times to Compensate for Training Data”

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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.

“Preparing for a Greener Future: Developing the Workforce for Clean Energy”

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Innovation in clean tech and renewable energy is moving fast — maybe a bit too fast. The clean tech industry is expected to create 8 million jobs by the end of 2030, according to a recent report by the International Energy Agency. These numbers are apparently based on current policies, and if more resources go toward the clean energy transition, the report’s authors expect the number to rise, too. The startup hires and trains folks to install and maintain sustainable heat pumps. It trains people new to the trades, provides upskilling training to those who have some experience, and has its workers install and maintain equipment for other companies.

“Revolutionizing the Aerospace Industry: In Orbit’s Mission as the Preferred Third-Party Logistics Partner for Science and Beyond”

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In Orbit Aerospace wants to be the third party logistics provider for science and industryTwo year old space startup In Orbit Aerospace wants to be the third party logistics provider for Earth to space commerce – and to get there, the company just closed a new agreement to validate key technical capabilities on the International Space Station. The El Segundo, California-based company is developing orbital platforms and re-entry vehicles to enable mass manufacturing and research in space. “Automation and robotics is the backbone of industrial manufacturing on Earth,” CEO Ryan Elliott said in a statement. On a slightly longer scale, In Orbit is aiming to launch a second mission in 2026 and then partner with a spacecraft provider to host a manufacturing lab on orbit. In Orbit is expecting that its core customers will be manufacturers, who will want to outsource on orbit hosting.

The Advent of Superhuman AI: OpenAI’s Mission to Develop Control Tools

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OpenAI formed the Superalignment team in July to develop ways to steer, regulate and govern “superintelligent” AI systems — that is, theoretical systems with intelligence far exceeding that of humans. Superalignment is a bit of touchy subject within the AI research community. “I think we’re going to reach human-level systems pretty soon, but it won’t stop there — we’re going to go right through to superhuman systems … So how do we align superhuman AI systems and make them safe? But the approach the team’s settled on for now involves using a weaker, less-sophisticated AI model (e.g. Well, it’s an analogy: the weak model is meant to be a stand-in for human supervisors while the strong model represents superintelligent AI.

“Reducing AI Risk: Distributional’s Mission to Create Protective Software”

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“Distributional is building the modern enterprise platform for AI testing and evaluation,” Clark told TechCrunch in an email interview. Our platform is built for AI product teams to proactively and continuously identify, understand and address AI risk before it harms their customers in production.”Clark was inspired to launch Distribution after encountering tech-related AI challenges at Intel post-SigOpt acquisition. While overseeing a team as Intel’s VP and GM of AI and high-performance compute, he found it nearly impossible to ensure that high-quality AI testing was taking place on a regular cadence. “The lessons I drew from my convergence of experiences pointed to the need for AI testing and evaluation,” Clark continued. The software offers organizations a “complete” view of AI risk, Clark says, in a pre-production environment that’s akin to a sandbox.