Everything

Muon Space closes $56M to scale all-in-one satellite platform

Space-as-a-service startup Muon Space closed a $56.7 million fundraising round to scale its satellite platform, while also announcing a new deal with defense giant Sierra Nevada Corp. 

California-based Muon designs, builds and operates satellites in low Earth orbit on behalf of customers. Some customers, like Hydrosat, provide their own payloads, while others, like the nonprofit coalition Earth Fire Alliance, use Muon-developed payloads. Muon’s business model represents a new paradigm for access to space: Instead of spending years developing satellite hardware and flight software, mission operations, and data processing, customers can use Muon’s end-to-end service instead. 

The startup says it has secured over $100 million in committed contracts from customers this year alone for its Halo satellite platform. That includes $60 million in deals announced earlier this year to design 10 remote-sensing satellites for unnamed customers. More recently, the company also announced a new deal with Sierra Nevada for the development of three spacecraft for the Vindlér remote sensing constellation. The first Vindlér satellite built by Muon is scheduled to launch in 2025. 

The Series B round was led by Activate Capital, with participation from Acme Capital and participating investors Costanoa Ventures, Radical Ventures and Congruent Ventures. It brings the company’s total capital raised to over $91 million, including a 2022 Series A round and a seed round in 2021. 

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Google loses massive antitrust case over search

Google has suffered a major court defeat in the U.S. that could alter the way it does business, should the decision stand.

Judge Amit P. Mehta of U.S. District Court for the District of Columbia, ruling in a case brought against Google by the Justice Department, said that Google had abused its monopoly power over the search business in part by paying companies to present its search engine as the default choice on their devices and web browsers. Mehta also agreed with the government’s arguments that Google collected data about consumers to cement its search engine’s dominance and illegally protected its monopoly over the ads that run inside Google Search results.

Google pays companies including Apple and Mozilla billions of dollars for prime placement in web browsers and on smartphones. According to The New York Times, Google paid Apple about $18 billion to be the default search engine on iPhones in 2021; Google shares 36% of search ad revenue from Safari with Apple.

“After having carefully considered and weighed the witness testimony and evidence, the court reaches the following conclusion: Google is a monopolist, and it has acted as one to maintain its monopoly,” Mehta wrote in his opinion filed Monday. “It has violated Section 2 of the Sherman Act.”

The ruling caps off a years-long case — U.S. et al. v. Google — that resulted in a 10-week trial last year. The Department of Justice and a group of attorneys general from 38 states and territories, led by Colorado and Nebraska, filed similar but separate antitrust suits against Google in 2020, alleging that Google unfairly blocked out would-be search rivals like Bing and DuckDuckGo. The Department of Justice estimated that Google had a 90% share of the search market, a figure that Google disputed.

Judge Mehta has yet to decide remedies for Google’s behavior. But he could force the company to change the way it runs its search business — or order it to sell off parts of that business. The ruling could be appealed, of course, and the final verdict may differ significantly, as happened with Microsoft’s famed antitrust case in the 1990s.

Google didn’t immediately respond to a request for comment.

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Announcing the agenda for the AI Stage at TechCrunch Disrupt 2024

We’re so excited to announce that we’ve added a dedicated AI Stage presented by Google Cloud to TechCrunch Disrupt 2024. It joins Fintech, SaaS and Space as the other industry-focused stages — all under one big roof.

We couldn’t possibly host TechCrunch Disrupt 2024 without a huge deep dive on all things artificial intelligence. So, here is our first sneak peek at the AI Stage agenda, happening all day on Wednesday, October 30. As a classic TechCrunch stage, we have some of the nascent industry’s heavy hitters, like Alexandr Wang and Aravind Srinivas, alongside our partners like Nebius AI and others!

Check the prelim agenda below and keep checking back for updates — we have a lot more to add to the AI Stage.

The AI Stage agenda at TechCrunch Disrupt 2024

From Search Engines to Knowledge Engines: Perplexity’s Rush Toward an AI-Curated Web

with Aravind Srinivas (Perplexity)

Perplexity‘s AI-powered search engine might be the next stage of interacting with the web and knowledge in general — or not. But the company is certainly risking it all to manifest that future, even if it ruffles a few feathers along the way. Hear from the CEO how the company plans to take on all comers in this new category of tech.

The Business of Labeling: A Deep Dive into Scale AI’s Massive Growth

with Alexandr Wang (Scale AI)

In 2016, when Scale AI was founded, few people could have predicted that the company, which builds tools to train, test and maintain generative AI models, would eventually grow into a $14 billion business. In hindsight, it seems almost inevitable that Scale would, well, scale quickly, given the dramatic growth many of its early customers, including OpenAI, experienced. In a conversation with Scale AI founder Alexandr Wang, we’ll discuss the company’s journey so far and the role that Scale AI now plays in the generative AI ecosystem.

How Generative AI Is Flooding the Web with Disinformation

with Pamela San Martin (Oversight Board), Imran Ahmed (CCDH), and speakers to be announced

As generative AI tools become more widely available — and become cheaper, or even free, to use — they’re being abused by an array of actors, including state actors, to create deepfakes and sow disinformation online. In this session, we’ll hear from experts about the types of deepfakes now circulating the web and some possible ways to combat the threat.

Are “Open” AI Models Really Better?

with Ali Farhadi (Allen Institute for Artificial Intelligence), Irene Solaiman (Hugging Face), and speakers to be announced

There’s a war brewing in the AI industry between companies in support of “open” AI models (models released under permissive licenses that can be fine-tuned and repurposed for a range of applications) and closed source models (models gated behind paid services and APIs). Is one approach better than the other? The answer isn’t as clear-cut as you might think. In this talk, we’ll investigate the differences between open and closed source models, as well as the subtle but important flavors of open-model licenses.

Navigating AI’s Legal and Ethical Minefield

with Sarah Myers West (AI Now), Jingna Zhang (Cara), and Ben Zhao (University of Chicago)

AI’s meteoric rise has created new ethical dilemmas and exacerbated old ones, while lawsuits drop left and right. This threatens both new and established AI companies, and the creators and workers whose labor feeds the models. A panel of experts in AI, copyright, and ethics take on this complex and fast-moving problem space.

But Is It Art? Generative AI’s Evolving Role in Music and Video Production

with Mikey Shulman (Suno), Amit Jain (Luma AI), and other speakers to be announced

Generative AI is increasingly capable of creating video, music, and other media on demand. But who actually wants it, and why? This panel of AI startups will discuss the growing markets for generative media and how they can be served without harming or displacing the artists they claim to empower.

About TechCrunch Disrupt 2024

TechCrunch Disrupt 2024 is where you’ll find innovation for every stage of your startup journey. Whether you’re a budding founder with a revolutionary idea, a seasoned startup looking to scale or an investor seeking the next big thing, TechCrunch Disrupt offers unparalleled resources, connections and expert insights to propel your venture forward. Over 10,000 startup leaders will be attending this year’s event on October 28-30 in San Francisco.

We can’t wait to hear from these AI leaders at this year’s show. Purchase your tickets here

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Placer.ai boosts valuation to $1.5B after quietly raising another $75M

Location data, for better or worse, continues to be a part of the bedrock of how apps are built. Now a startup developing AI market research based on that location data, Placer.ai, has quietly raised $75 million at an expanded valuation of nearly $1.5 billion, TechCrunch has learned.

The startup provides a wide range of location-based analytics to companies in verticals like retail, events and entertainment, CPG, retail estate, financial services and healthcare by combining AI with anonymised data that it sources from third party apps.

We first became aware of the funding by way of a Form D filed in July detailing Placer’s intentions to raise $75 million. We have confirmed with the company’s CEO and CFO that it has closed the full amount, with a new valuation of $1.45 billion, up nearly 50% since its last round, a $100 million Series C made at a $1 billion valuation. 

The investment underscores the growing value of location data for businesses beyond the app publishers themselves. And, at a time when more people are aware of data protection around mobile apps, not least due to a growing number of data breaches, it also serves as a reminder of just how much data we generate just through modern life.

Placer’s analytics cover general trends like foot traffic at a particular location or for a particular store — factoids like Aldi currently ranking as the fastest-growing retailer based on visits — but also more detailed data about who buys what and and when, people’s demographic profiles and more.

Such methods are a little creepy, as some have noted, but also not totally uncommon. (Others that track location data include Foursquare, Esri and many others offer location analytics.)

Like other mobile analytics firms, the startup picks up data by way of an SDK that it installs with hundreds of app publishers; as well as through other third-party sources. It describes itself as a “privacy by design” business: all of the data it uses is anonymised before it comes to Placer, the company said.

The company declined to disclose specific participants in this latest fundraise except to note that existing backers participated. PitchBook notes that real estate investment firm GEM Realty Capital is also in this most recent round. 

Overall, Placer has more than 50 investors — both firms and individuals — on its cap table. They include Josh Buckley (the former CEO of Product Hunt), WndrCo (Jeffrey Katzenberg’s investment firm), Lachy Groom, MMC Technology Ventures, Fifth Wall Ventures and Array Ventures, alongside J.M. Schapiro (CEO of Continental Realty Corp), Eliot Bencuya and Jeff Karsh of Tryperion Partners, Daniel Klein of Klein Enterprises/Sundeck Capital and Majestic Realty.

Numbers have been strong for the company. Placer’s CEO and co-founder Noam Ben-Zvi told TechCrunch in an interview that the company crossed an annual revenue run rate of $100 million in February, and it has grown 80% in the last year and expects to grow another 60% this year. It has also passed 4,300 customers (up from 1,000 in 2022 when it raised the $100 million). The list includes the likes of Sony, various city development organizations, Wegmans, and Century 21. 

“What ties them together is that they all have a stake in the physical world,” he said. 

The funding was raised based on inbound interest, CFO Dean Nese said. The plan will be to use the funding for business development and to add more features and data sets to the platform. It says it already provides users with “hundreds” of these data sets.

Placer was founded in 2018 by Ben-Zvi and fellow Israelis Zohar Bar-Yehuda (Data Scientist), Oded Fossfeld (CTO) and Ofir Lemel (CPO), and it was just two years later that the company faced what you might assume would be a death-knell for a location analytics company: the arrival of the Covid-19 pandemic and the world turning away from physical gatherings. It turned out to be the opposite.

At an especially restricted time, Ben-Zvi said, “Our data provided a lot of visibility into what was working and what was not working.”

Having that foothold with customers meant that the company expanded its reach along with the world “reopening” for business.

While Placer has always used machine learning and inference to build more detailed profiles based on the data that they glean from apps, that has now also been a strong point with its end users, who have been given a green light to explore how to build more AI into their workflows. 

“Customers want a holistic one stop-shop platform for market research,” he said. “They may ask themselves: Should I expand to this market? How are my competitors doing? What they want is all the underlying data that’s relevant, and all the aggregations and the tools on top. Analytics is a core ingredient.”

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Apple’s new Safari feature removes distracting items from websites

Safari’s newest feature, Distraction Control, can remove distracting elements from a website. The feature follows Browser Company’s Arc Browse’s addition of Boosts last year, which similarly lets users remove features from a site and further customize its appearance.

Apple is rolling out the early version of the feature this week through new developer betas of iOS 18, iPadOS 18 and macOS Sequoia.

Users can access the Distraction Control tool from the Page Menu in the Smart Search field. They then select the item on the website they want to remove. Safari will remember to remove the elements the next time they visit the site. The choice doesn’t currently sync across hardware, however, so users will have to hide the elements on each new device.

Users can click on the blue Hide icon in the search field and select “Show hidden items” to unhide any of the web page’s elements.

Apple said that the feature won’t remove ads or sections that have frequently changing content. It’s not clear if this tool will be able to remove, for example, a section like “Who to follow” or “Explore” on X, as these elements appear in the same place on the home page, but the content within those boxes is dynamic.

Arc Browser’s Boost tool was able to remove these sections during our last testing last year.

With iOS 18, Apple also introduced a redesigned reader for better listening and font controls. It also launched Highlights, a feature that will surface important information from a page, including quick links for driving directions, call information and summaries of TV show reviews mentioned on a page.

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YouTuber files class action suit over OpenAI’s scrape of creators’ transcripts

A YouTube creator is seeking to bring a class action lawsuit against OpenAI, alleging that the company trained its generative AI models on millions of transcripts from YouTube videos without notifying or compensating the videos’ owners.

In a complaint filed Friday in the U.S. District Court for the Northern District of California, attorneys for David Millette, a YouTube user based in Massachusetts, allege that OpenAI surreptitiously transcribed Millette’s and other creators’ videos to train the models that power the company’s AI-powered chatbot platform, ChatGPT, and other generative AI tools and products. By collecting this data, OpenAI “profited significantly” from the creators’ work, the complaint alleges, while violating copyright law and YouTube’s terms of service that prohibit the use of videos for apps independent of its service.

“As [OpenAI’s] AI products become more sophisticated through the use of training data sets, they become more valuable to prospective and current users, who purchase subscriptions to access [OpenAI’s] AI products,” the complaint reads. “Much of the material in OpenAI’s training data sets, however, comes from works that were copied by OpenAI without consent, without credit, and without compensation.”

Millette, represented by the law firm Bursor & Fisher, is seeking a jury trial and over $5 million in damages for all YouTube users and creators whose data might’ve been swept up in OpenAI’s training.

Generative AI models like OpenAI’s have no real intelligence. Fed an enormous number of examples (e.g. movies, voice recordings, essays and so on), models “learn” how likely data is to occur based on patterns, including the context of any surrounding data.

Most models are trained on data sourced from public websites and data sets around the web. Companies argue that fair use shields their efforts to scrape data indiscriminately and use it for training commercial models. Many copyright holders disagree, however — and they’re filing suits aimed at halting practice.

Video transcriptions have become a key training data ingredient as other data wells dry up, so to speak.

More than 35% of the world’s top 1,000 websites now block OpenAI’s web crawler, according to data from Originality.AI. And around 25% of data from “high-quality” sources has been restricted from the major data sets used to train AI models, a study by MIT’s Data Provenance Initiative found. Should the current access-blocking trend continue, the research group Epoch AI predicts that developers will run out of data to train generative AI models between 2026 and 2032.

In April, The New York Times reported that OpenAI created its first speech recognition model, Whisper, for the purpose of transcribing audio from videos to collect additional training data. An OpenAI team that included company’s president, Greg Brockman, transcribed more than a million hours of video from YouTube using Whisper, according to The Times, and used the transcripts to train OpenAI’s text-generating and -analyzing model GPT-4.

Some OpenAI staffers discussed how such a move might go against YouTube’s rules, per the Times.

In July, Proof News reported that companies including Anthropic, Apple, Salesforce and Nvidia used a data set called The Pile, which contains subtitles from hundreds of thousands of YouTube videos, to train generative AI models. Many YouTube creators whose subtitles were swept up in The Pile weren’t aware of and didn’t consent to this; Apple later released a statement saying that it didn’t intend to use those models to power any AI features in its products.

Google, YouTube’s parent company, has also sought to use transcripts to train its models.

Last year, Google broadened its terms of service (ToS) partly to allow the company to tap more user data for generative AI model training. Under the old ToS, it wasn’t clear whether Google could use YouTube data to build products beyond the video platform. Not so under the new terms, which loosen the reins considerably. 

We’ve reached out to OpenAI and Google for comment on the class action suit and will update this piece if they respond.

It’s been a rough start to the month for OpenAI.

Tesla and X CEO Elon Musk on Monday filed a new suit against OpenAI and CEO Sam Altman accusing the company of abandoning its original nonprofit mission by reserving some of its most sophisticated tech for commercial customers. Musk made the same claims in a February lawsuit against OpenAI, but the new suit alleges that OpenAI is engaging in racketeering activity, as well.

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TechCrunch Minute: The iPad was the surprising star of Apple’s sales numbers

For once, the iPad was the highlight of Apple’s latest sales numbers.

The company said in its third quarter earnings report that iPad sales increased year-over-year, from $5.8 billion to $7.2 billion. The reason for that growth is probably new versions of the iPad Air and iPad Pro, which were announced in May. Turns out that if Apple actually invests in iPads, they sell.

In contrast, global iPhone sales were down for the second quarter in a row, falling to $39.3 billion. As you can tell by comparing those numbers, smartphones are still a lot more important to Apple’s bottom line.

So why are iPhone sales down? Apple’s biggest challenge seems to be in China, which is its third largest market, and a country where iPhones face growing competition from Chinese companies like Huawei. Apple has responded to that competition by aggressively cutting prices, which resulted in strong sales in May.

Hit play to learn more, then let us know what you think in the comments!

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Flipkart blitzes into India’s 10-minute quick commerce battle

India’s fast-growing quick commerce market is getting a new deep-pocketed entrant: Walmart-owned Flipkart, India’s largest e-commerce firm.

Flipkart has started to roll out Flipkart Minutes, its quick commerce service, in parts of Bengaluru. The new service offers customers the ability to have a wide range of items, from grocery to smartphones, delivered to them within 10 to 15 minutes. The e-commerce firm is offering customers free delivery on orders priced at Rs 100, or $1.20.

Flipkart is the latest entrant to the instant commerce market, which is quickly making inroads in India even as the model has failed in many other markets. Quick commerce players, which rely on hundreds of small warehouses or “dark stores” strategically located near residential and business areas for rapid deliveries, have expanded to numerous categories in recent months, including fashion and electronics, increasingly entering Amazon’s and Flipkart’s traditional territory.

Flipkart didn’t immediately respond to a request for comment. TechCrunch reported in March that Flipkart was working on a quick commerce offering.

This move comes at a time when the quick commerce sector in India is showing remarkable resilience and growth. The convenience of 10-minute grocery deliveries has struck a chord with urban Indian consumers, leading to encouraging signs for companies like Zomato-owned Blinkit, StepStone-backed Zepto and SoftBank-backed Swiggy Instamart.

Analysts and investors love the space, too. Goldman Sachs estimates that Blinkit, the leading quick commerce player in India, is already worth more than its parent firm’s eponymous food delivery operations. Zomato’s stock hit all-time high to as much as $30 billion in market cap last week after the firm, which acquired Blinkit for less than $600 million in 2022, reported a quarterly profit of about $30 million.

Flipkart MinutesImage Credits: TechCrunch

Flipkart leads the e-commerce market in India, but Amazon has a stronger grip on urban Indian customers. The Bengaluru-based startup sees quick commerce as a way to win some of Amazon’s top India customers, according to a person familiar with the matter.

Amazon, for its part, has shown little interest in entering the quick commerce space in India, instead focusing on same-day delivery for Prime members and questioning the quality of products from “fast” delivery services in its marketing campaigns. The world’s largest e-commerce firm is separately in talks to acquire a stake in Swiggy, which has confidentially filed for an initial public offering, according to people familiar with the matter.

A recent TechCrunch analysis found that many of Amazon India’s bestselling items were available on quick commerce platforms, meaning that the company stands to lose some business and traffic to quick commerce companies.

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38 startups have become unicorns so far in 2024: Here’s the full list

Despite the tight venture capital market, unicorns are still being created every month.

Using data from Crunchbase, CB Insights, and PitchBook, TechCrunch tracked down the newly minted unicorns so far this year. The list includes Elon Musk’s xAI, which is already valued at a staggering $24 billion, as well as a good number of other AI startups. But cybersecurity, health tech and fintech have also done well. This list will be updated throughout the year, so check back and see the powerhouses raising this year! 

July

Aven — $1 billion: Aven, founded in 2019, is a consumer credit card company. It reached a $1 billion valuation after closing a $142 million Series D led by Khosla Ventures and General Catalyst, according to CB Insights.

Flo Health — $1 billion: This fertility-tracking app announced a $200 million Series C, valuing the company at more than $1 billion, TechCrunch reported. Founded in 2015, the company has raised more than $290 million in total funding from investors, including General Atlantic. 

Altana Technologies — $1 billion: This global supply chain management company, founded in 2018, closed a $200 million Series C, valuing it at $1 billion. Investors included Salesforce Ventures and the US Innovative Technology Fund. PitchBook notes the company has raised around $322 million to date.

Chainguard — $1.1 billion: This cybersecurity company announced a $140 million Series C, valuing the company at $1.12 billion. Founded in 2021, Chainguard has raised more than $256 million to date from investors, including Sequoia Capital, Lightspeed Venture Partners, and Redpoint Ventures. 

Harvey — $1.5 billion: Legal AI platform Harvey raised a $100 million round from investors, including Google Ventures, OpenAI, Kleiner Perkins, Sequoia Capital, that brought its valuation to $1.5 billion. It has now raised a total of $206 million.  

Saronic Technologies — $1 billion: Saronic, a defense tech maker of autonomous surface vessels, raised a $175 million Series B at a $1 billion valuation, led by Andreessen Horowitz, with other backers including 8VC, Caffeinated Capital and Elad Gil. It has now raised $244.5 million to date, according to PitchBook.

June

Huntress — $1.55 billion: The managed cybersecurity startup that offers extended detection and response (EDR) tech closed a $150 million Series D, valuing the company at $1.55 billion. The company has raised a little more than $300 million to date. Launched in 2015, it has top investors on its cap table, including Kleiner Perkins and Sapphire Ventures, according to PitchBook.  

xAI — $24 billion: Founded only last year by Elon Musk, this AI startup is already valued at $24 billion after closing a $6 billion Series B backed by investors like Andreessen Horowitz, Craft Ventures, Fidelity Investments, and Sequoia. xAI offers the multimodal large language model known as Grok.

BillionToOne — $1 billion: This disease-screening genetic testing company raised a $130 million Series D, according to Crunchbase, valuing the company at $1 billion. 

May

Altruist — $1.5 billion: This fintech startup, which offers investment management for independent registered investment advisers, was founded in 2018. It raised a $169 million Series E in May, led by ICONIQ Growth, valuing the company at $1.5 billion. The company has also received investments from Insight Partners and Endeavor Catalyst, according to PitchBook, and has raised more than $450 million to date in funding.

Weka — $1.6 billion:  A SaaS data storage company that specializes in AI use cases, Weka closed a $140 million Series E, valuing the company at $1.6 billion, according to PitchBook. Launched in 2013, the company has raised around $375 million to date, with investors including Valor Equity Partners, Generation Investment Management, and Nvidia. 

Farcaster — $1 billion: The open source, blockchain-based social media startup closed a $150 million Series A led by Paradigm, leading to a post-money valuation of $1 billion. Launched in 2021, it’s backed by a16z and Union Square Ventures and has raised more than $180 million in funding to date, according to PitchBook. 

Sigma Computing — $1.5 billion: This AI-driven big data analytics startup raised a round in May that valued it at $1.5 billion. The company has raised almost $560 million to date, according to Crunchbase. 

Humanity Protocol — $1 billion: This blockchain palm-scanning identity startup, founded in 2023, raised a $30 million seed round, giving it a post-money valuation of $1 billion. In total, the company has only raised $30 million from investors, including hedge fund Ash Park Capital and Aza Ventures, according to PitchBook. 

April

Cyera — $1.5 billion:  Data security provider Cyera raised a $300 million Series C in April, valuing the company at $1.5 billion, according to PitchBook. Founded in 2021, the company has raised $460 million in funding to date from investors, including Redpoint Ventures and Accel. 

Monad Labs — $3 billion: Monad, which is working on a faster version of the Ethereum blockchain, raised a $225 million Series A in April, valuing the company at $3 billion. To date, the company has raised more than $244 million from investors, including Amber Group and Artichoke Capital. 

Nexamp — $1.5 billion: This clean-energy company raised a $520 million round with a mixture of debt and venture financing that valued the company at $1.08 billion, according to PitchBook. The company, founded in 2007, has raised a little more than $1.31 billion in funding to date. 

Grow Therapy — $1.4 billion: This therapist-finder health tech company launched in 2020 and raised an $88 million Series C round in April, according to PitchBook, valuing the company at $1.4 billion. To date, the company has raised almost $180 million in funding from investors, including Sequoia, Goldman Sachs, and actress Anna Kendrick. 

Cognition AI — $2 billion: Cognition, which is working on an AI software engineer named Devin, reportedly raised a $175 million Series B in April, valuing the company at $2 billion. To date, the company, founded in 2023, has raised $196 million, according to PitchBook, from investors such as Founders Fund, Khosla Ventures and Pear. 

Xaira Therapeutics — $2.7 billion: This AI drug discovery startup, founded in 2023, launched with a huge $1 billion Series A in April, giving it a valuation of $2.7 billion. The company has raised $1 billion in total funding from investors ARCH Venture Partners, Foresite Labs, Menlo Ventures, Lux Capital, and New Enterprise Associates. 

Flip — $1.19 billion: This social commerce platform, founded in 2019, raised a $144 million Series C, valuing the company at $1.19 billion, according to PitchBook. To date, the company has raised a little more than $300 million in venture funding from investors, including ad tech giant AppLovin, Streamlined VC, Mubadala sovereign wealth fund. 

March

io.net — $1 billion: This cloud service, which puts GPUs from data centers and cryptocurrency miners into a decentralized network that can be used by AI models, was founded in 2019. (It used to be geared toward quant trading). It closed a $33 million Series A in March, according to PitchBook, valuing the company at $1 billion. The company has only raised $35 million to date, with investors including 6th Man Ventures, Foresight Ventures, and ArkStream Capital, according to PitchBook. 

Perplexity — $1 billion: The famed AI search engine raised a $73.6 million Series B in January at a $520 million valuation, followed by an additional $62.7 million in April, doubling Perplexity‘s valuation to $1.04 billion. The company has raised $165 million to date. 

Octane — $1.1 billion: A company that offers instant financing on mowers and recreational vehicles, Octane raised $50 million in April, giving in a post-money valuation of $1.11 billion. The company, launched in 2014, has raised around $250 million million in funding to date, from investors including Progressive and Gaingels, according to PitchBook. 

Celestial AI — $1.2 billion: The AI company raised a $175 million Series C in March, valuing it at $1.2 billion, led by billionaire Thomas Tull’s USIT fund. The company has raised $339 million to date from investors, including Koch Disruptive Technologies, Temasek, AMD, Samsung Catalyst Fund and Porsche Automobil Holding.

IntraBio — $1 billion: Intra bio, a neurodegenerative diseases drug discovery company, raised a $40 million round of funding in March that reportedly valued it at $1 billion, according to Crunchbase. To date, the company has raised more than $50 million in funding.

Liquid Death — $1.4 billion:  TechCrunch reported that the beverage startup’s last round of $67 million valued the company at $1.4 billion. Liquid Death has raised more than $260 million in funding, according to Crunchbase. 

February

Blink Health — $1.3 billion: Founded in 2014, this online pharmacy took on $81 million in private equity funding, giving it a $1.28 billion post-money valuation. The company, which has now received a mixture of private equity and venture capital funding, has raised more than $250 million in funding to date, with investors including 8VC and BoxGroup, according to PitchBook. 

NinjaOne — $1.9 billion: This mobile device management and security company raised a $231 million Series C in February, giving it a $1.9 billion post-money valuation, it said. The company has raised $282.7 million to date from investors, including ICONIQ Growth, according to PitchBook.  

Ascend Elements — $1.6 billion:  This sustainable battery company raised a $162 million round in February, it said. This gives it a post-money valuation of $1.61 billion, according to PitchBook. To date, the company has raised more than $1 billion in funding from investors, including Just Climate, Clearvision Ventures, and Irongrey. 

Lambda — $1.5 billion:  This GPU cloud computing platform for AI use raised a $320 million Series C in February at a post-money valuation of $1.52 billion. It then raised another $800 million round in July, according to PitchBook. In total, the company has raised almost $900 million, with investors including Garry Tan, Bloomberg Beta, and Alumni Ventures. 

EigenLayer — $1.1 billion: EigenLayer is behind a new project for Ethereum called staking, which involves using Ether tokens as security. Launched in 2021, it picked up a $100 million Series B in February, led by a16z, giving it a $1 billion valuation, according to PitchBook. In total, the company has raised a little more than $160 million in venture funding, with other backers including Blockchain Capital and Apollo Crypto. 

Figure — $2.6 billion: The humanoid robot company raised a $675 million Series B in February, giving it a valuation of $2.6 billion. In total, Figure has raised almost $850 million in venture funding, with investors including Bezos Expeditions, Calm Ventures, Intel, Nvidia, OpenAI and Microsoft, according to PitchBook. 

Together AI — $1.25 billion: This cloud service for running open source AI models raised a $106 million round led by Salesforce Ventures, giving the company a post-money valuation of $1.25 billion. Together AI has raised a little more than $232 million in venture funding from investors, including Hugging Face, NEA Partners, and 137 Ventures, according to PitchBook.  

Bugcrowd — $1 billion: This crowdsourced bug-fixing cybersecurity platform raised a $102 million Series E in February, led by General Catalyst, which valued the company at $1 billion, according to Crunchbase. The company has raised more than $180 million to date. 

January

ElevenLabs — $1 billion: The AI text-to-speech generator startup, specializing in language dubbing, picked up an $80 million Series B in January, giving it a post-money valuation of $1 billion. ElevenLabs has raised $101 million to date, with investors like a16z, Sequoia, and SV Angel, according to Crunchbase. 

Quantinuum — $5.3 billion: Founded in 2021, the quantum computing cloud service raised a $300 million round in January led by Honeywell, valuing the company at $5.3 billion, according to Crunchbase. PitchBook shows that IMB Ventures and JPMorgan Chase are also backers of the company. 

Zūm — $1.3 billion: This school transportation fleet management startup closed a $140 million Series E round in January led by Singapore firm GIC, valuing Zūm at $1.3 billion, the company said. It has raised $350 million in total, according to Crunchbase. 

This piece was updated to correct the numbers about Huntress’ valuation and Lambda‘s name.

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AWS unveils Mithra to identify and mitigate malicious domains across its massive system

When a company is the size of Amazon, a lot of bad actors will come after it and its customers, which makes defending the network a monster job. Over the years Amazon has developed a number of strategies, from machine learning and monitoring tools to good old-fashioned phone calling to identify and reduce risks to their network.

The company on Monday revealed an internal umbrella platform for the first time that has been in place for several years, called Mithra, which it built to handle Amazon scale. The main piece of technology underlying the solution is a massive graph database with 3.5 billion nodes and 48 billion edges, according to C.J. Moses, Amazon’s chief information security officer (CISO). (Mithra runs on internal systems inside Amazon as opposed to being a service that customers pay for directly.)

Moses says in simple terms that Mithra is basically a big funnel. “We have to go from lots of data down to very small amounts of data. The further you get down that funnel, the more you’re able to then have humans become engaged to be able to make the final decisions on what needs to be done,” Moses told TechCrunch.

In some cases, where the software has a strong signal that a domain is bad, humans don’t even need to be involved in the decision making; at Amazon’s scale, taking humans out of the loop when it can is important. “If you get down to where you have strong assurance that a domain is bad, we’re able to take that data and very quickly transition it straight into the systems that protect our environments,” Moses said.

That could involve the web application firewall (WAF), Amazon GuardDuty, the company’s threat detection system or even forwarding the domain in question to the AWS security service team for further review when required. Moses says when you combine Mithra with Sonaris, the company’s network observation platform, it provides a “pretty good defensive net around our AWS and Amazon environments.”

Amazon scale is unique.The company deals with a quarter of all internet traffic every day, according to Moses, and it “observes up to 200 trillion DNS requests in a single AWS Region alone. Mithra detects an average of 182,000 new malicious domains daily.”

The company has been using a combination of AI, ML, algorithms, monitoring and other tooling, but as it grows and scales, it realized it needed to have a single platform dedicated to monitoring the system for malicious domains and snuffing them out whenever possible. That’s where Mithra comes in.

AI plays a big role in a system this large, of course, and the company wouldn’t be able to deal with such a large graph database without AI. “The reality is that AI, in this particular case, or in many cases like this, is exactly the type of technology that you want to use in order to look at large scale amounts of data and identify throughout that data, the things that should be interesting to us,” Moses said. “And we can obviously train the AI to look for the aberrations, to look for the things that are outside of the norm, or those things that we’ve previously seen as malicious.”

The AI models can also help humans make better decisions. “Are we going to block this domain or not? Here’s a preponderance of the data that’s been assembled from Mithra, from Sonaris, from other threat sensors that we have, and then use that AI to coalesce it together into recommendations to the different systems that take the defensive measures,” Moses said.

Generative AI has a role to play because it enables the threat analysts, who are doing the threat hunting, to interact with the data in plain language and get back answers to help understand the situation better. Previously they would have had to run scripts, but generative AI provides a faster way to see what’s happening.

Sometimes, it’s not about shutting down domains, or how sophisticated the tech is, but just being able to pick up the phone and call a fellow CISO about what his team is seeing. “Some of our biggest investment is in making sure we have a very viable CISO network so we can pick up the phone and call someone at 2 a.m. and not have it be a cold call, even if they’re not customers of ours,” he said.

Update: This story has been updated to clarify when Mithra was launched.

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