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Robotic Automations

Agora raises $34B Series B to keep building the Carta for real estate | TechCrunch


Since he was very young, Bar Mor knew that he would inevitably do something with real estate. His family was involved in all types of real estate projects, from ground-up construction to managing residential, commercial and retail properties. But unlike his parents, Mor also had a passion for technology. His interest in tech was reinforced […]

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Software Development in Sri Lanka

Robotic Automations

LanceDB, which counts Midjourney as a customer, is building databases for multimodal AI | TechCrunch


Chang She, previously the VP of engineering at Tubi and a Cloudera veteran, has years of experience building data tooling and infrastructure. But when She began working in the AI space, he quickly ran into problems with traditional data infrastructure — problems that prevented him from bringing AI models into production. “Machine learning engineers and […]

© 2024 TechCrunch. All rights reserved. For personal use only.


Software Development in Sri Lanka

Robotic Automations

OpenAI says it's building a tool to let content creators 'opt out' of AI training | TechCrunch


OpenAI says it’s developing a tool to let creators better control how their content is used in AI.

Called Media Manager, the tool — once it’s released — will allow creators and content owners to identify their works to OpenAI and specify how they want those works to be included or excluded from AI research and training. The goal is to have the tool in place by 2025, OpenAI says, as the company works with creators, content owners and regulators toward a common standard.

“This will require cutting-edge machine learning research to build a first-ever tool of its kind to help us identify copyrighted text, images, audio and video across multiple sources and reflect creator preferences,” OpenAI writes in a blog post. “Over time, we plan to introduce additional choices and features.”


Software Development in Sri Lanka

Robotic Automations

Amae Health is building an in-person approach to mental healthcare in an increasingly digital space | TechCrunch


When Sonia García and Stas Sokolin decided to launch Amae Health to solve the broken care system for people with severe mental illness, they were already intimately familiar with the industry’s issues.

“I started thinking about this problem a very long time ago,” said Sokolin, Amae’s CEO. “I grew up with a sister who had bipolar disorder for many, many years, and as a family we always struggled to find her care. It seemed like everything was so piecemeal, and it broke our family apart.”

Garcia had her own experiences with the mental healthcare system, too. She lost her father to suicide when she was 16 years old, and then she and her family spent years as caregivers for her brother with schizoaffective and bipolar disorder. Sokolin and García were introduced by mutual friends at Stanford because they were both passionate about this area. The pair knew the system could be better.

They launched Amae Health in 2022 to be a new approach to helping patients with severe mental illness. Amae brings resources — including family and individual therapy, social workers, psychiatric care and medicine management — all under one roof. One physical roof, that is, as Amae is focused on an in-person approach. The startup hired Dr. Scott Fears, who had experience with this all-encompassing care approach through his work with the Los Angeles Veterans Affair Hospital, so they could iterate on and improve an existing model as opposed to starting a new one from scratch.

Amae Health just raised a $15 million Series A round led by Quiet Capital with participation from Healthier Capital, former One Medical CEO Amir Dan Rubin’s firm; Baszucki Group and Index Ventures partner Mike Volpi, in addition to all of the company’s seed investors. The startup currently has one clinic in Los Angeles and plans to use the capital to expand. Its next center will be in Raleigh, North Carolina, with locations in Houston, Ohio and New York to follow shortly after.

The funds will also be used to continue building out the company’s data platform. Sokolin said the company is using AI to go through the troves of data it collects at its clinic to find ways they can continue to improve care.

Over the past few years, many startups have launched to improve the mental healthcare system, but Amae Health’s focus area and approach stand out. Most of the mental health startups that launched in the pandemic are digital first and focused on anxiety and depression. Amae looks very different.

There’s nothing wrong, of course, with having a slate of companies focused on anxiety and depression, and it’s good to see founders focused on helping people with severe mental illness, too. Severe mental health problems affect 14.1 million people in the U.S., according to the National Alliance on Mental Illness. But there’s a lot less innovation in the sector.

That’s not too surprising: Solutions for people with severe mental illness don’t perfectly fit a traditional venture model in the way many telemedicine and digital solutions do. People with severe mental illness need care that is in person, making solutions more costly and slower to scale.

“When we first went out to raise money, a lot of venture investors were asking, why are you doing this in person? Why is this not virtual?” Sokolin said. “The fact of the matter is you can’t treat someone who is having delusions or auditory hallucinations virtually. The same way you can’t treat cancer virtually, you can’t treat this virtually.”

The nature of the business also means that they aren’t expanding to all 50 states right away as some digital health startups have been able to. García said the company is fine with that because it’s more focused on the outcomes than the scaling.

“That is about intentional growth and scale, not the winner-take-all market, but really being considerate and conscious about how we do grow and ensuring we are generating lasting change and recovery in these individuals’ lives,” Garcia said.

Trying to scale too fast has hurt some mental health startups. Therapy telemedicine platform Cerebral has come under fire for how it advertises to potential customers and how it handles patient data in its pursuit of scale.

This slower growth approach can and has worked in venture before, said Sokolin, a former VC at both the Chan Zuckerberg Initiative and Health2047. One Medical, a full-service healthcare system, including in-person care, is a prime example. The company raised more than $500 million before getting scooped up by Amazon for $3.9 billion. It’s not surprising the former CEO is a current investor in Amae.

Sokolin and García are fine with the fact that their approach has turned off some potential investors. They are focused more on building a system for quality care, not just how many patients they can see.

“There are way more individuals than anyone could ever treat,” Sokolin said about the scope of individuals with severe mental illness. “We are never going to treat anything more than a small fraction, but we want to be the best-in-class provider for those members.”


Software Development in Sri Lanka

Robotic Automations

Dropbox, Figma CEOs back Lamini, a startup building a generative AI platform for enterprises | TechCrunch


Lamini, a Palo Alto-based startup building a platform to help enterprises deploy generative AI tech, has raised $25 million from investors including Stanford computer science professor Andrew Ng.

Lamini, co-founded several years ago by Sharon Zhou and Greg Diamos, has an interesting sales pitch.

Many generative AI platforms are far too general-purpose, Zhou and Diamos argue, and don’t have solutions and infrastructure geared to meet the needs of corporations. In contrast, Lamini was built from the ground up with enterprises in mind, and is focused on delivering high generative AI accuracy and scalability.

“The top priority of nearly every CEO, CIO and CTO is to take advantage of generative AI within their organization with maximal ROI,” Zhou, Lamini’s CEO, told TechCrunch. “But while it’s easy to get a working demo on a laptop for an individual developer, the path to production is strewn with failures left and right.”

To Zhou’s point, many companies have expressed frustration with the hurdles to meaningfully embracing generative AI across their business functions.

According to a March poll from MIT Insights, only 9% of organizations have widely adopted generative AI despite 75% having experimented with it. Top hurdles run the gamut from a lack of IT infrastructure and capabilities to poor governance structures, insufficient skills and high implementation costs. Security is a major factor, too — in a recent survey by Insight Enterprises, 38% of companies said security was impacting their ability to leverage generative AI tech.

So what’s Lamini’s answer?

Zhou says that “every piece” of Lamini’s tech stack has been optimized for enterprise-scale generative AI workloads, from the hardware to the software, including the engines used to support model orchestration, fine-tuning, running and training. “Optimized” is a vague word, granted, but Lamini is pioneering one step that Zhou calls “memory tuning,” which is a technique to train a model on data such that it recalls parts of that data exactly.

Memory tuning can potentially reduce hallucinations, Zhou claims, or instances when a model makes up facts in response to a request.

“Memory tuning is a training paradigm — as efficient as fine-tuning, but goes beyond it — to train a model on proprietary data that includes key facts, numbers and figures so that the model has high precision,” Nina Wei, an AI designer at Lamini, told me via email, “and can memorize and recall the exact match of any key information instead of generalizing or hallucinating.”

I’m not sure I buy that. “Memory tuning” appears to be more a marketing term than an academic one; there aren’t any research papers about it — none that I managed to turn up, at least. I’ll leave Lamini to show evidence that its “memory tuning” is better than the other hallucination-reducing techniques that are being/have been attempted.

Fortunately for Lamini, memory tuning isn’t its only differentiator.

Zhou says the platform can operate in highly secured environments, including air-gapped ones. Lamini lets companies run, fine tune, and train models on a range of configurations, from on-premises data centers to public and private clouds. And it scales workloads “elastically,” reaching over 1,000 GPUs if the application or use case demands it, Zhou says.

“Incentives are currently misaligned in the market with closed source models,” Zhou said. “We aim to put control back into the hands of more people, not just a few, starting with enterprises who care most about control and have the most to lose from their proprietary data owned by someone else.”

Lamini’s co-founders are, for what it’s worth, quite accomplished in the AI space. They’ve also separately brushed shoulders with Ng, which no doubt explains his investment.

Zhou was previously faculty at Stanford, where she headed a group that was researching generative AI. Prior to receiving her doctorate in computer science under Ng, she was a machine learning product manager at Google Cloud.

Diamos, for his part, co-founded MLCommons, the engineering consortium dedicated to creating standard benchmarks for AI models and hardware, as well as the MLCommons benchmarking suite, MLPerf. He also led AI research at Baidu, where he worked with Ng while the latter was chief scientist there. Diamos was also a software architect on Nvidia’s CUDA team.

The co-founders’ industry connections appear to have given Lamini a leg up on the fundraising front. In addition to Ng, Figma CEO Dylan Field, Dropbox CEO Drew Houston, OpenAI co-founder Andrej Karpathy, and — strangely enough — Bernard Arnault, the CEO of luxury goods giant LVMH, have all invested in Lamini.

AMD Ventures is also an investor (a bit ironic considering Diamos’ Nvidia roots), as are First Round Capital and Amplify Partners. AMD got involved early, supplying Lamini with data center hardware, and today, Lamini runs many of its models on AMD Instinct GPUs, bucking the industry trend.

Lamini makes the lofty claim that its model training and running performance is on par with Nvidia equivalent GPUs, depending on the workload. Since we’re not equipped to test that claim, we’ll leave it to third parties.

To date, Lamini has raised $25 million across seed and Series A rounds (Amplify led the Series A). Zhou says the money is being put toward tripling the company’s 10-person team, expanding its compute infrastructure, and kicking off development into “deeper technical optimizations.”

There are a number of enterprise-oriented, generative AI vendors that could compete with aspects of Lamini’s platform, including tech giants like Google, AWS and Microsoft (via its OpenAI partnership). Google, AWS and OpenAI, in particular, have been aggressively courting the enterprise in recent months, introducing features like streamlined fine-tuning, private fine-tuning on private data, and more.

I asked Zhou about Lamini’s customers, revenue and overall go-to-market momentum. She wasn’t willing to reveal much at this somewhat early juncture, but said that AMD (via the AMD Ventures tie-in), AngelList and NordicTrack are among Lamini’s early (paying) users, along with several undisclosed government agencies.

“We’re growing quickly,” she added. “The number one challenge is serving customers. We’ve only handled inbound demand because we’ve been inundated. Given the interest in generative AI, we’re not representative in the overall tech slowdown — unlike our peers in the hyped AI world, we have gross margins and burn that look more like a regular tech company.”

Amplify general partner Mike Dauber said, “We believe there’s a massive opportunity for generative AI in enterprises. While there are a number of AI infrastructure companies, Lamini is the first one I’ve seen that is taking the problems of the enterprise seriously and creating a solution that helps enterprises unlock the tremendous value of their private data while satisfying even the most stringent compliance and security requirements.”


Software Development in Sri Lanka

Robotic Automations

Midi is building a digital platform for an oft-overlooked area of women's health | TechCrunch


When Joanna Strober was around 47 she stopped sleeping. While losing sleep is a common symptom of perimenopause, she first had to go to multiple providers, including driving 45 minutes out of San Francisco to pay $750 out of pocket, to get that diagnosis and proper treatment.

“That feeling of wow, I’ve really been suffering unnecessarily for the past year really stuck with me,” Strober said on a recent episode of TechCrunch’s Found podcast. “I started talking to all my friends and trying to understand what’s going on with them and what became clear is that perimenopause and menopause is this big thing. It kind of hits women like it’s pile of bricks. There’s lots of different symptoms to it and they’re very few providers who are trained to take care of this population.”

That realization is what inspired Strober to launch Midi Health, a telehealth platform designed to serve women in midlife by connecting them with providers that are trained in perimenopause and menopause symptoms and treatments.

Despite her “aha” moment, Strober explained why she couldn’t launch the startup right away. She said that Midi couldn’t have existed had the U.S. government not have changed its rules surrounding telehealth and where people could access care during the pandemic. Because of the changes surrounding digital health, Strober said the company was able to launch its platform that brought care to women as opposed to women having to find in-person care.

“Understanding that this problem that had been around for a long time and could finally be addressed using telehealth was a very exciting revelation,” Strober said. “And that’s why I wanted to start this company.”

Midi operates a little bit differently than many of the other digital health companies started in the post-pandemic wave, Strober said. She said Midi isn’t set up to be a digital avenue for users to get one-off care or treatment as fast as possible like many other companies of the same era, but rather to be a platform where women build long-term relationships with providers that make them feel seen.

This approach is also why Strober thinks Midi has been able to keep growing and raising VC funds as VCs have become less interested in the category. The company recently raised a $60 million Series B round led by Emerson Collective with participation from Google Ventures, SteelSky Ventures, and Muse Capital, among others. This round brings the company’s total funding to $99 million.

Digital health startup raised $13.2 billion globally in 2023, according to CB Insights data. This marks a decrease of 48% from 2022, $25.5 billion, and a decrease of 75% from 2021 when a record $52.7 billion was invested.

“I think too few telehealth companies didn’t think about that long-term customer relationship,” Strober said. “We view ourselves as building a healthcare trusted brand. So our brand is expert care for women. We need to give you that amazing care so you come back to us over and over and over again. That is what women are doing.”

Midi isn’t Strober’s first digital health startup and she talked about how her past experience building Kurbo Health, a startup focused on child obesity before digital health was even a thing, influenced her choices in building Midi. She also talked about how her past life as a venture capitalist also played a role in how she approached the business.

With this latest round of funding, Midi looks forward to expanding care in areas that fall under perimenopause and menopause including things like sexual wellness, hair and skin care and access to testosterone.

“People keep on asking, you know, when are you leaving perimenopause, and menopause?” Strober said. “But perimenopause and menopause is a big market. So we are working a lot on understanding what are the health needs of women during this period of their life and how do we appropriately rise to meet those concerns.”


Software Development in Sri Lanka

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