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Elastic founder on returning to open source four years after going proprietary
Licensing kerfuffles have long been a defining facet of the commercial open source space. Some of the biggest vendors have switched to a more restrictive “copyleft” license, as Grafana and Element have done, or gone full proprietary, as HashiCorp did last year with Terraform.
But one $8 billion company has gone the other way.
Elastic, the creator of enterprise search and data retrieval engine Elasticsearch and the Kibana visualization dashboard, threw a surprise curveball last month when it revealed it was going open source once more — nearly four years after switching to a couple of proprietary “source available” licenses. The move goes against a grain that has seen countless companies ditch open source altogether. Some are even creating a whole new licensing paradigm, as we’re seeing with “fair source,” which has been adopted by several startups.
“It was just taking too long”
In 2021, Elastic moved to closed source licenses after several years of conflict with Amazon’s cloud subsidiary AWS, which was selling its own managed version of Elasticsearch. While AWS was perfectly within its rights to do so given the permissive nature of the Apache 2.0 license, Elastic took umbrage at the way that AWS was marketing its incarnation, using branding such as “Amazon Elasticsearch.” Elastic believed this was causing too much confusion, as customers and end users don’t always pay too much attention to the intricacies of open source projects and the associated commercial services.
“People sometimes think that we changed the license because we were upset with Amazon for taking our open source project and providing it ‘as a service,’” Elastic co-founder and CTO Shay Banon told TechCrunch in an interview this week. “To be honest, I was always okay with it, because it’s in the license that they’re allowed to do that. The thing we always struggled with was just the trademark violation.”
Elastic pursued legal avenues to get Amazon to retreat from the Elasticsearch brand, a scenario reminiscent of the ongoing WordPress brouhaha we’ve seen this past week. And while Elastic later settled its trademark spat with AWS, such legal wrangles consume a lot of resources, when all the company wanted to do was safeguard its brand.
“When we looked at the legal route, we felt like we had a really good case, and it was actually one that we ended up winning, but that wasn’t really relevant anymore because of the change we’d made [to the Elasticsearch license],” Banon said. “But it was just taking too long — you can spend four years winning a legal case, and by then you’ve lost the market due to confusion.”
Back to the future
The change was always something of a sore point internally, as the company was forced to use language such as “free and open” rather than “open source.” But the change worked as Elastic had hoped, forcing AWS to fork Elasticsearch and create a variant dubbed OpenSearch, which the cloud giant transitioned over to the Linux Foundation just this month.
With enough time having passed, and OpenSearch now firmly established, Banon and company decided to reverse course and make Elasticsearch open source once more.
“We knew that Amazon would fork Elasticsearch, but it’s not like there was a huge masterplan here — I did hope, though, that if enough time passed with the fork, we could maybe return to open source,” Banon said. “And to be honest, it’s for a very selfish reason — I love open source.”
Elastic hasn’t quite gone “full” circle, though. Rather than re-adopting its permissive Apache 2.0 license of yore, the company has gone with AGPL, which has greater restrictions — it requires that any derivative software be released under the same AGPL license.
For the past four years, Elastic has given customers a choice between its proprietary Elastic license or the SSPL (server side public license), which was created by MongoDB and subsequently failed to get approved as “open source” by the Open Source Initiative (OSI), the stewards of the official open source definition. While SSPL already offers some of the benefits of an open source license, such as the ability to view and modify code, with the addition of AGPL, Elastic gets to call itself open source once again — the license is recognized as such by the OSI.
“The Elastic [and SSPL] licenses were already very permissive and allowed you to use Elasticsearch for free; they just didn’t have the stamp of ‘open source,’” Banon said. “We know about this space so much, but most users don’t — they just Google ‘open source vector database,’ they see a list, and they choose between them because they care about open source. And that’s why I care about being on that list.”
Moving forward, Elastic says that it’s hoping to work with the OSI toward creating a new license, or at least having a discussion about which licenses do and don’t get to be classed as open source. The perfect license, according to Banon, is one that sits “somewhere between AGPL and SSPL,” though he concedes that AGPL in itself may actually be sufficient for the most part.
But for now, Banon says that simply being able to call itself “open source” again is good enough.
“It’s still magical to say ‘open source’ — ‘open source search,’ ‘open source infrastructure monitoring,’ ‘open source security,’” Banon said. “It encapsulates a lot in two words — it encapsulates the code being open, and all the community aspects. It encapsulates a set of freedoms that we developers love having.”
Tech
Can an Apple lawsuit derail OpenAI’s hardware plans?
Apple recently filed a trade secrets lawsuit against OpenAI, accusing the AI company of a pattern of misconduct aimed at getting current and former Apple employees to share confidential information. (In response, OpenAI said it is “not aware of any evidence that this complaint has merit.”)
On the latest episode of TechCrunch’s Equity podcast, Kirsten Korosec, Sean O’Kane, and I debated whether this lawsuit will cast a shadow over OpenAI’s much-discussed plans to get into the hardware business (starting with a mobile smart speaker) and go public.
“Even setting aside whether or not the court grants any kind of injunctive relief or any kind of restraining order over what OpenAI is doing, it just naturally can lead to that sort of situation where it’s going to cause some delays in what OpenAI is working on,” Sean suggested. “Which I’m sure was probably part of the reasoning behind Apple doing this. They don’t do this stuff willy nilly.”
With all those plans on the line, will OpenAI try to settle this as quickly as possible, or did it learn from its recent courtroom victory against Elon Musk that it can endure the cost and embarrassment of a trial? Kirsten, at least, predicts the latter.
Keep reading for a preview of our conversation, edited for length and clarity.
Kirsten: Sean, how do you feel about Sam Altman listening to you with a little device maybe in your pocket?
Sean: I’m good. Maybe that’s predictable, but I’m good. No thanks.
We’ll get into it, I’m sure, but this is allegedly the first product that OpenAI has been working on in its hardware division with Jony Ive and company. They’ve been really coy ever since that weird video they put out last year of them sitting at that coffee shop or bar in San Francisco and sort of talking very vaguely about hardware and legacy devices, meaning laptops and phones. And so if this is the direction they’re headed in, all power to people who want to have somebody like that always listening to them. This is not going to be for me.
Anthony: Part of what we have to remember about those kinds of devices is also that, depending on how mobile it is, it’s not just listening to you, it’s listening to the people around you. I might be fine with it — I’m not fine with it, but let’s say I was — but then if we met up in-person at Disrupt, then suddenly it might be listening to all of us.
There are all kinds of social norms that are going to have to be renegotiated if these things become widespread. I think we should make fun of and criticize people who record other people without consent.
Kirsten: Well, I bring up the device that has been speculated about for a really long time, and we’ll see what it really ends up being once it’s officially introduced, but it’s important in the context of this lawsuit that Apple filed last Friday.
It was the biggest news of the week, certainly, and this is a trade secret lawsuit. It has some pretty wild allegations and we should very much emphasize these are allegations that have been filed in a complaint by Apple. But what it is accusing OpenAI of is a pattern of misconduct at the highest levels, specifically directed towards OpenAI employees who used to work at Apple. And in fact they’ve named the chief hardware officer Tang Tan in this lawsuit.
This is all important because Apple is accusing OpenAI of essentially stealing their trade secrets, but in the context of that, this could be then used for a competing hardware product. I’m wondering if maybe we don’t get into whether this lawsuit has merits, because we haven’t gone through full discovery, but what are your initial impressions of the lawsuit aside from the fact that wow, this is going to be entertaining?
Sean: Two things. One, this is a pretty big risk potentially to whatever it is OpenAI is working on. Even setting aside whether or not the court grants any kind of injunctive relief or any kind of restraining order over what OpenAI is doing, it just naturally can lead to that sort of situation where it’s going to cause some delays in what OpenAI is working on, which I’m sure was probably part of the reasoning behind Apple doing this. They don’t do this stuff willy nilly.
The other is that we think that OpenAI is — we know that they’ve filed confidentially for an IPO. We think it might happen as early as the end of this year, or early next year, if you believe Sam Altman’s cautious language around the IPO. And this just raises a whole bunch of questions around that because, on the one hand, we think their business right now is probably overwhelmingly the software; they’re not really factoring in any hardware business into that picture at the moment.
They’re about to go to the markets and they’re going to be pitching bankers and investors on where they think their addressable market should be, and if they have a big amount of that pegged to a potential hardware division and hardware products, this could be a huge risk to that and changes a lot of the calculus of sort of how the IPO gets priced. So that’s where my head’s at.
Anthony: One [allegation] that I assume that Apple must have pretty solid numbers on is, they said more than 400 Apple employees now work at OpenAI. Granted, both of them are very large companies with many thousands or tens of thousands of employees. So as a percentage, it’s not necessarily huge. But that seems like a lot of people and a pretty serious talent drain.
And the other thing I’m wondering is related to Sean’s point. With the context of the potential IPO, how much damage did OpenAI ultimately take from a marketing and brand perspective from the trial it already went through? That it seemed to basically win, but there was a lot of not-terrible-but-kind-of-embarrassing dirty laundry that came out in the testimony. To what extent are they just like, “We do not want to go through that again”? Or did they take the lesson of, “Hey, we went through it and we survived and we’ll be okay if we have to do another trial with Apple”?
Kirsten: I fully predict the latter, by the way.
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Tech
What to watch for after Jensen Huang’s Japan visit
Nvidia’s chief Jensen Huang spent two days — July 15 and 16 — in Tokyo, courting Japan’s industrial and chip-supply elite, weeks after a keynote in Taiwan, and months after a visit to South Korea. He left with deals spanning Japan’s entire tech ecosystem: a national AI factory, partnerships with the country’s leading robotics companies, and agreements with the chip-material suppliers powering Nvidia’s next generation of AI chips. His message was clear. Nvidia is targeting Japan’s factory floor, and many of the country’s biggest manufacturers are joining in. AI’s next chapter, Huang said, belongs to factory floors, robots, and machines, and he wants Japan to build it.
Thirty years ago, a $5 million Sega investment helped keep a near-bankrupt Nvidia afloat; today, Nvidia and Japan’s industrial giants need each other again — this time to build the physical-AI era, starting with these three projects:
Noetra — Japan’s sovereign-AI play. The country doesn’t want to run its factories and robots on American or Chinese AI. So, the government pulled together roughly 44 domestic firms, with SoftBank, Sony, NEC, and Honda at the core, to build its own AI for robots, vehicles, and factory floors. Tokyo is committing up to 1 trillion yen ($6.2 billion) over five years, a bet on homegrown “physical AI,” foundation models built to run machines. Japan wants to own the software brain. The hardware to build it, though, still comes from Nvidia. The U.S. chip giant is building “a Vera Rubin AI factory,” a massive data center packed with its next-generation chips, expected to launch in 2028, with 13,750 Vera CPUs and 27,500 Rubin GPUs, delivering 140 megawatts. Noetra will oversee the effort, with plans to build the data center. Noetra’s plan runs in three stages: a reasoning model heavy on Japanese-language skills starting in fiscal 2026; an omni-modal version handling text, images, video, and audio by 2028; and “Real-world Native AI” built to run robots by 2030, released to outside Noetra developers in phases.
The robotics coalition — Japan’s industrial giants line up behind Cosmos. Nvidia is targeting Japan’s factory floor, and many of the country’s top robotics and manufacturing players are signing on. Fanuc, Yaskawa, Kawasaki Heavy, Fujitsu, Hitachi, NEC, Sony, SoftBank, Kubota, and robotics group AIRoA say they plan to build on Nvidia’s Cosmos models, an open-model effort Nvidia started in May with a handful of global AI labs. In Tokyo, Nvidia gave them a reason to commit, unveiling Cosmos 3 Edge, a version of the model that runs on its Jetson Thor chips inside the machines themselves. Some are already testing a shared control system; others, like Honda R&D and Omron, are building on the tools now. “The next frontier of AI is in the physical world, and this is a once-in-a-generation opportunity for Japan,” Huang said in the company’s statement. “Japan invented modern manufacturing. Now, it has the opportunity to reinvent it for the age of intelligent industries.”
Toyota — cars and physical AI. Toyota uses Nvidia chips across much of its stack. It committed its next-generation vehicles to Nvidia’s Drive platform at CES in January 2025; the newer work extends Nvidia into its manufacturing, where simulations are used to design production lines, into the software that runs its vehicles, and into systems that read road traffic. Toyota’s cars will run advanced driver assistance, which steers and brakes but still requires a driver, a more conservative approach than Waymo and Tesla, which are developing systems that rely less on a human driver.
Huang’s visit put physical AI at the center of Japan’s industrial strategy, and Tokyo is spending to back it. Facing a shrinking workforce, Japan wants 10 million AI-equipped robots across 18 sectors by 2040, backed by $65 billion in public and private physical-AI investment.
The longer game is bigger. Japan’s AI Robotics Strategy, released in March, aims to capture more than 30% of the global AI robotics market by 2040, a market Tokyo values at roughly ¥20 trillion, or about $133 billion. METI is funding a domestic foundation model to run the machines, and Noetra’s Nvidia-powered factory is where models of that scale, into the trillions of parameters, would be trained.
Underneath the industrial case is a sovereign one. As the U.S. and China pull ahead in large-scale AI, Tokyo wants its own data, its own compute, and less dependence on infrastructure it doesn’t control. Huang appeared on July 16 alongside trade minister Ryosei Akazawa at the government’s physical-AI launch, with Prime Minister Sanae Takaichi joining by video. The Takaichi administration has made AI and semiconductors the centerpiece of a growth plan chasing ¥370 trillion ($2.3 trillion) in public and private investment by 2040. Noetra’s factory — which Nvidia bills as “the world’s first national AI infrastructure” — is the clearest bet yet. Japan’s push for independence, at least for now, rests on American chips.
In two days, Huang sat across from nearly every name that matters in Japanese tech — the CEOs of Toyota, Fanuc, Yaskawa, Fujitsu, and Kawasaki over lunch, and dozens of supply-chain chiefs over skewers and whisky in a Kanda izakaya.
It’s the same playbook he ran weeks earlier — a homecoming keynote in Taiwan, fried chicken, and a 50,000-GPU deal in Seoul last fall. This time, it was Tokyo’s turn, with the robots, the supply chain, and the chips underneath.
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Tech
Netflix paid $587M for Ben Affleck’s AI filmmaking startup
In a new regulatory filing, Netflix revealed that it paid $587 million in cash for InterPositive, a startup co-founded by actor and director Ben Affleck.
The streaming company announced the acquisition in March, with a statement from Affleck saying he wanted to “protect the power of human creativity.” According to Affleck, InterPublic’s AI tools help filmmakers improve their footage in post-production, particularly when it comes to making up for “real-world production challenges such as missing shots, background replacements or incorrect lighting.”
At the time, Netflix announced that the entire InterPositive team would be joining the company, with Affleck joining as a senior advisor, but it didn’t disclose the financial terms of the deal. A subsequent report in Bloomberg suggested that the deal could be worth up to $600 million.
In its most recent earnings report, Netflix said that around 300 of its titles have already used generative AI.
