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Gradient raises $10M to let companies deploy and fine-tune multiple LLMs

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Gradient, a startup that allows developers to build and customize AI apps in the cloud using large language models (LLMs), today emerged from stealth with $10 million in funding led by Wing VC with participation from Mango Capital, Tokyo Black, The New Normal Fund, Secure Octane and Global Founders Capital.

Chris Change, Gradient’s CEO, co-founded the company alongside Mark Huang and Forrest Moret several months ago while working on AI products at Big Tech firms including Netflix, Splunk, and Google. The trio came to the realization that LLMs like OpenAI’s GPT-4 could be transformative for the enterprise, but believed that getting the most out of LLMs would require creating a reliable way to add private, proprietary data to them.

“Traditionally, teams have focused on improving a single, generalist model — and existing solutions support this model,” Chang told TechCrunch via email. “This is largely because it was too complex to manage multi-model systems. However, relying on a single model is suboptimal because there’s an inevitable tradeoff in task-specific performance.”

Chang, Huang and Moret designed Gradient, then, to make it easier for teams to deploy “specialized” and fine-tuned LLMs at scale. The platform runs in the cloud, allowing an organization to develop and integrate as many as “thousands” of LLMs into a single system, Chang says.

Gradient customers don’t have to train LLMs from scratch. The platform hosts a number of open source LLMs including Meta’s Llama 2, which users can fine-tune to their needs. Gradient also offers models aimed at particular use cases (like data reconciliation, context-gathering and paperwork processing) and industries (like finance and law).

Gradient can host and serve models through an API a la Hugging Face, CoreWeave and other AI infrastructure providers. Or it can deploy AI systems in an organization’s’ public cloud environment, whether Google Cloud Platform, Azure or AWS.

In either case, customers maintain “full ownership” and control over their data and trained models, Chang says.

“The barriers to development are far too high for AI today,” he added. “Building high-performance, custom AI is inaccessible due to the high complexity and cost of setting up the necessary infrastructure and developing new models. We’ve seen that the vast majority of businesses understand the value AI can bring to their business, but struggle to realize the value due to the complexity of adoption. Our platform radically simplifies harnessing AI for a business, which is a tremendous value-add.”

Now, you might ask — like this reporter did — what sets Gradient apart from the other startups engineering tools to pair LLMs with in-house data? And what about the many other companies already customizing LLMs for enterprise clients as a service? It’s a reasonable question.

Take a look at Reka, for example, which recently emerged from stealth to work with companies to build custom-tailored LLM-powered apps. Writer lets customers fine-tune LLMs on their own content and style guides. Contextual AI, Fixie and LlamaIndex, which recently emerged from stealth, are developing tools to allow companies to add their own data to existing LLMs. And Cohere trains LLMs to customers’ specifications.

They’re not the only ones. OpenAI offers a range of model fine-tuning tools, as do incumbents like Google (via Vertex AI), Amazon (via Bedrock) and Microsoft (via the Azure OpenAI Service).

Chang makes that case that Gradient is one of the few platforms that lets companies “productionize” multiple models at once. And, he asserts, it’s affordable — the platform is priced on-demand such that users only pay for the infrastructure they use. (Larger customers have the option of paying for dedicated capacity.)

But even if Gradient isn’t drastically different from its rivals in the LLM dev space, it stands to benefit — and is benefiting — from the massive influx in interest around generative AI, including LLMs. Nearly a fifth of total global VC funding this year has come from the AI sector alone, according to Crunchbase. And PitchBook expects the generative AI market to reach $42.6 billion in 2023.

“Gradient makes it much easier to develop complex AI systems that leverage many ‘expert LLMs,’” he said. “This approach ensures the AI system consistently achieves the highest performance for each task, all in a single platform … Our platform is designed to make it extremely easy for teams to deploy specialized LLMs, purpose-built for their specific problems, more effectively.”

Gradient claims to be working with around 20 enterprise customers at the moment with “thousands” of users combined. Its near-term goal is scaling the cloud backend and growing its team from 17 full-time employees to 25 by the end of the year.

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Where Did Earth’s Oceans Come From? Scientists Say They Originated From Comets

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Scientists have long debated how Earth became rich in liquid water after the planet formed about 4.5 billion years ago. Now a new research published in Science Advances suggests that comets, particularly those from the Jupiter family, may have played a significant role in delivering water to Earth.

The study focused on Comet 67P/Churyumov-Gerasimenko, a celestial body that belongs to the Jupiter family of comets.

Using data from the European Space Agency‘s (ESA) Rosetta mission, researchers analysed the molecular structure of water on the comet and found striking similarities to the water in Earth’s oceans. This discovery strengthens the theory that icy comets and asteroids crashing into Earth contributed to the formation of its oceans.

The ratio of deuterium to regular hydrogen in the water is a key signature which is the basis of the study. Deuterium is a heavier isotope of hydrogen and it forms heavy water.

Previous studies had shown that the levels of deuterium in the water vapour of many Jupiter-family comets closely matched those found in Earth’s water. To explore this connection further, NASA planetary scientist Kathleen Mandt and her team used advanced statistical techniques to analyse data from Comet 67P.

The findings revealed that deuterium-rich water was more closely associated with dust grains around the comet than previously understood. Because water with deuterium is more likely to form in cold environments, there’s a higher concentration of the isotope on objects that formed far from the Sun, such as comets, than in objects that formed closer to the Sun, like asteroids.

Measurements within the last couple of decades of deuterium in the water vapor of several other Jupiter-family comets showed similar levels to Earth’s water.

This discovery not only strengthens the idea that comets helped deliver water to Earth but also provides valuable insight into how the early solar system formed. By studying the molecular makeup of comets like 67P, scientists can better understand the processes that shaped our planet and its oceans billions of years ago.

Mandt expressed her excitement about the results, saying, “This is just one of those very rare cases where you propose a hypothesis and actually find it happening.” The research also shows how studying comets can help unravel mysteries about the building blocks of the solar system.

ALSO SEE: Uranus Is Hiding 8000-Km Deep Ocean? New Study Presents Thrilling Hints

ALSO SEE: Webb Telescope Sees World That Could Reek Of Burnt Matches And Rotten Eggs

(Image: NASA)





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Chainalysis permanently parts ways with its founding CEO

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Michael Gronager, the co-founder and longtime CEO of Chainalysis, has agreed to leave the company permanently, two months after taking a temporary personal leave of absence.

Chainalysis, a buzzy 10-year-old, New York-based blockchain data platform, will now be led by co-founder Jonathan Levin, as Levin told TechCrunch, explaining that on Tuesday, its board of directors gave him Gronager’s job. But Levin, who has long served as the outfit’s chief strategy officer, will do more than run the company as CEO; he will also maintain his other roles.

“I’ve been running R&D, and I think the CEO should be the chief product officer, so I’m making no changes to our R&D leadership team; it will continue to report directly to me,” he said in an interview on Wednesday.

Levin declined to provide more information about Gronager other than to say that Gronager is also no longer on the Chainalysis board but retains his equity in the company.

A message to Gronager on Wednesday from TechCrunch went unreturned.

Asked about Chainalysis’ financial health, Levin said the startup is “continuing to invest in our growth,” and that “we don’t need to raise capital. We raised $175 million in 2022 and [still] feel strong about the cash position of company.” He added that his focus will be on “executing, the expansion of our risk platform, and going deeper with our government clients across the world to ensure they can deal with the increased demand of crypto.”

Chainalysis, whose early investors include Benchmark, was valued by investors at $8.6 billion during that 2022 funding round. Crypto investor Katie Haun, who first discovered Chainalysis in her capacity as federal prosecutor, reportedly began buying up secondary shares of the company at a valuation of $2.5 billion this past April.

Considered a “crypto detective,” one whose clients include the U.S. government and a wide range of corporations, Chainalysis in late 2023 laid off slightly more than 15% of its staff of 900, with plans to focus more squarely on government contracting, according to The Block.

The entire crypto industry has been in bounce-back mode in more recent weeks, as the incoming Trump administration signals a far friendlier stance toward digital currencies. The most obvious proof point: The price of bitcoin reached a record high of $100,000 on Wednesday.

Above: Levin at a StrictlyVC event hosted by TechCrunch in November 2024.



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Zopa, the UK neobank, snaps up $87M at a $1B+ valuation, eschewing the IPO route

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Some believe Klarna’s planned IPO in 2025 could set the stage for other fintech startups to go public. But with the tech IPO market still sluggish, one of the candidates hotly tipped to follow suit has instead just announced a fundraise, and its CEO says going public is “not a priority.” Zopa, the U.K. neobank […]

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