California lawmakers and AV industry battle for future of self-driving trucks

A California bill that would require a trained human safety operator to be present any time a heavy-duty autonomous vehicle operates on public roads in the state is getting traction. The bill, first introduced in January, passed the state’s Assembly Wednesday and will now face a committee review and vote in the Senate.

Advocates of the bill want to ensure both the safety of California road users and the job security of truck drivers. AV companies and industry representatives say the move is unreasonable, threatens California’s competitiveness in the AV and trucking space, and hinders the advancement of a technology that can save lives.

“AB 316 is a preemptive technology ban that will put California even further behind other states and lock in the devastating safety status quo on California’s roads, which saw more than 4,400 people die last year,” said Jeff Farrah, executive director of the Autonomous Vehicle Industry Association, in a statement. “AB 316 undermines California’s law enforcement and safety officials as they seek to regulate and conduct oversight over life-saving autonomous trucks.”

If the legislation passes in the Senate, it’ll go to Gov. Gavin Newsom’s desk to be signed into law, unless Newsom decides to veto. While Newsom has received huge donations from big tech companies and recently buddied up to tech billionaire Elon Musk, the politician has also been known to crack down on technology that puts his constituents at risk.

Risk and safety is what the conversation around AB 316 comes down to. Bill authors and supporters have pointed to instances when robotaxis malfunctioned on city streets in San Francisco and Teslas operating under the automaker’s advanced driver assistance systems like Autopilot have caused fatal accidents.

“California highways are an unpredictable place, but as a Teamster truck driver of 13 years, I’m trained to expect the unexpected. I know to look out for people texting while driving, potholes in the middle of the road, and folks on the side of the highway with a flat tire. We can’t trust new technology to pick up on those things,” said Fernando Reyes, Commercial Driver and Teamsters Local 350 member, in a statement. “My truck weighs well over 10,000 pounds. The thought of it barreling down the highway with no driver behind the wheel is a terrifying thought, and it isn’t safe. AB 316 is the only way forward for California.”

The bill does not ban companies from testing or deploying self-driving trucks on California’s public roads. It only insists that a trained human driver be present in the vehicle to take over in case of an emergency.

The California Department of Motor Vehicles, the agency tasked with providing testing and deployment permits for AVs in the state, still has a ban on autonomous vehicles weighing over 10,001 pounds in the state. In anticipation of the DMV soon lifting that ban, AB 316 effectively limits the DMV’s future authority to regulate AVs, power the agency has held since 2012. If passed, the DMV would not be able to sign off on autonomous trucking companies removing the driver for testing or deployment purposes unless the legislature is convinced that it’s safe enough to do so.

Additional language was added to AB 316 to outline the role the DMV will play in providing evidence of safety to policymakers.

By January 1, 2029, or five years after the start of testing (whichever occurs later), the DMV will need to submit a report to the state that evaluates the performance of AV technology and its impact on public safety and employment in the trucking sector. The report will include information like disengagements and crashes, as well as a recommendation on whether the legislature should “remove, modify or maintain the requirement for an autonomous vehicle with a gross weight of 10,001 pounds or more to operate with a human safety operator physically present in the vehicle,” according to the bill’s language.

Once that report is handed over, the legislature will conduct an oversight hearing. If the legislature and the governor approve of removing the human safety operator requirement, the DMV will still need to wait another year after the date of the hearing to issue a permit. That means California might not see autonomous trucks operating with no human in the front seat until 2030 at the earliest.

“If enacted, AB 316 will make California an outlier by prohibiting autonomous trucks from operating on their own unless approved by the [California Legislature] through a convoluted process,” said Safer Roads for All, a coalition of AV advocates. “Let’s hope other states are more sensible and let road safety experts do their jobs.”

Self-driving truck companies face a potential roadblock in California

California lawmakers and AV industry battle for future of self-driving trucks by Rebecca Bellan originally published on TechCrunch

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Indian SaaS startup Capillary Technologies grabs $45M to expand globally

Capillary Technologies, an Indian SaaS startup that offers solutions for loyalty management and customer engagement, has raised $45 million in a funding round, as it plans to expand into global markets and widen its reach through mergers and acquisitions. The funding arrives at a crucial time amidst the prevailing market slowdown, where startups, particularly those at the late stage, are facing a capital crunch.

Capillary’s Series D funding round was led by Avataar Ventures and its LPs Pantheon, 57Stars and Unigestion. It also saw participation from Filter Capital and Innoven Capital. The round comprises $40 million in equity and about $5–$7 million in debt. With the latest capital injection, the startup has raised nearly $150 million in capital to date.

Founded in 2012, Capillary Technologies initially focused on the retail vertical in India and Southeast Asia. In recent years, it has broadened its offerings and launched in more markets including the Middle East and South Africa, and since early 2021, the U.S.

Capillary is carving a distinctive niche in the market with its emphasis on gamification to bolster customer loyalty, a strategy it says it has been able to deploy across commerce, retail, aviation and hospitality sectors.

The Bengaluru-based startup’s suite of technology-driven, cloud-native solutions has helped it attract a number of clients. Already, it has collaborated with over 250 brands across 30 countries, powering more than 100 loyalty programs. High-profile clients include Domino’s, Tata Group, Puma, Shell, Petron and Marks & Spencers. Capillary’s tech reaches over a billion customers and clocks over 5 billion transactions annually.

“The way most of our competitors in the U.S. and elsewhere have built in as like a services business where customers ask you something, and you build it. On the other hand, we have taken a very product view to it,” Capillary Technologies founder and managing director Aneesh Reddy said in an interview.

Just over a couple of years after entering the U.S. and acquiring the customer experience startup Persuade, Capillary’s business has grown by 3.5x, the startup said, without disclosing specific numbers. It also says the U.S. now accounts for more than a third of its revenues.

The startup has made five acquisitions in the U.S., with the last one of Texas-based loyalty solutions provider Brierley from Nomura announced in April this year. These acquisitions have helped it to introduce solutions to clients operating in wider verticals.

Reddy told TechCrunch that Capillary is seeking to leverage the fresh funding to expand its presence in the U.S. and Europe through actively pursuing strategic acquisitions, as part of its growth strategy.

“The core business is profitable and growing by itself, so most of the funding is going to be used for acquisitions,” he said. “As you would guess, if you have the money, this is a great time to buy.”

In late 2021, Capillary Technologies filed its draft papers to go public in India. The startup has, though, delayed that plan due to the ongoing market slowdown. Reddy said the idea of filing an IPO in India is still being considered and he may executive that within the next three years.

“The good piece of Capillary is it’s profitable. With this fundraise, we have a lot of excess cash also on the balance sheet. So, it’s not like I have a gun to my head to list,” he said.

Capillary has a headcount of over 750 people, including 200 contractors, and has offices in Dubai, Indonesia, Malaysia, and Singapore, apart from India and the U.S. It counts Sequoia Capital and Warburg Pincus among its existing backers.

“It has been truly remarkable witnessing Capillary’s business transformation over the past four years,” said Mohan Kumar, Managing Partner at Avataar Ventures, in a statement.

“The strategic decision to diversify from Asia into the US and Europe, encompassing various consumer verticals beyond retail, has been nothing short of impressive. This move has catapulted Capillary into a leadership position in Loyalty software and this has been recognized by external mentions like the Forrester Wave. Given the expanded addressable market and the immense potential that lies ahead, Avataar is wholeheartedly committed to supporting Capillary in its pursuit to become a global market leader.”

Indian SaaS startup Capillary Technologies grabs $45M to expand globally by Jagmeet Singh originally published on TechCrunch

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Indian SaaS startup Capillary Technologies grabs $45M to expand globally

Capillary Technologies, an Indian SaaS startup that offers solutions for loyalty management and customer engagement, has raised $45 million in a funding round, as it plans to expand into global markets and widen its reach through mergers and acquisitions. The funding arrives at a crucial time amidst the prevailing market slowdown, where startups, particularly those at the late stage, are facing a capital crunch.

Capillary’s Series D funding round was led by Avataar Ventures and its LPs Pantheon, 57Stars and Unigestion. It also saw participation from Filter Capital and Innoven Capital. The round comprises $40 million in equity and about $5–$7 million in debt. With the latest capital injection, the startup has raised nearly $150 million in capital to date.

Founded in 2012, Capillary Technologies initially focused on the retail vertical in India and Southeast Asia. In recent years, it has broadened its offerings and launched in more markets including the Middle East and South Africa, and since early 2021, the U.S.

Capillary is carving a distinctive niche in the market with its emphasis on gamification to bolster customer loyalty, a strategy it says it has been able to deploy across commerce, retail, aviation and hospitality sectors.

The Bengaluru-based startup’s suite of technology-driven, cloud-native solutions has helped it attract a number of clients. Already, it has collaborated with over 250 brands across 30 countries, powering more than 100 loyalty programs. High-profile clients include Domino’s, Tata Group, Puma, Shell, Petron and Marks & Spencers. Capillary’s tech reaches over a billion customers and clocks over 5 billion transactions annually.

“The way most of our competitors in the U.S. and elsewhere have built in as like a services business where customers ask you something, and you build it. On the other hand, we have taken a very product view to it,” Capillary Technologies founder and managing director Aneesh Reddy said in an interview.

Just over a couple of years after entering the U.S. and acquiring the customer experience startup Persuade, Capillary’s business has grown by 3.5x, the startup said, without disclosing specific numbers. It also says the U.S. now accounts for more than a third of its revenues.

The startup has made five acquisitions in the U.S., with the last one of Texas-based loyalty solutions provider Brierley from Nomura announced in April this year. These acquisitions have helped it to introduce solutions to clients operating in wider verticals.

Reddy told TechCrunch that Capillary is seeking to leverage the fresh funding to expand its presence in the U.S. and Europe through actively pursuing strategic acquisitions, as part of its growth strategy.

“The core business is profitable and growing by itself, so most of the funding is going to be used for acquisitions,” he said. “As you would guess, if you have the money, this is a great time to buy.”

In late 2021, Capillary Technologies filed its draft papers to go public in India. The startup has, though, delayed that plan due to the ongoing market slowdown. Reddy said the idea of filing an IPO in India is still being considered and he may executive that within the next three years.

“The good piece of Capillary is it’s profitable. With this fundraise, we have a lot of excess cash also on the balance sheet. So, it’s not like I have a gun to my head to list,” he said.

Capillary has a headcount of over 750 people, including 200 contractors, and has offices in Dubai, Indonesia, Malaysia, and Singapore, apart from India and the U.S. It counts Sequoia Capital and Warburg Pincus among its existing backers.

“It has been truly remarkable witnessing Capillary’s business transformation over the past four years,” said Mohan Kumar, Managing Partner at Avataar Ventures, in a statement.

“The strategic decision to diversify from Asia into the US and Europe, encompassing various consumer verticals beyond retail, has been nothing short of impressive. This move has catapulted Capillary into a leadership position in Loyalty software and this has been recognized by external mentions like the Forrester Wave. Given the expanded addressable market and the immense potential that lies ahead, Avataar is wholeheartedly committed to supporting Capillary in its pursuit to become a global market leader.”

Indian SaaS startup Capillary Technologies grabs $45M to expand globally by Jagmeet Singh originally published on TechCrunch

source https://techcrunch.com/2023/05/31/capillary-technologies-funding-series-d/

Lightmatter’s photonic AI hardware is ready to shine with $154M in new funding

Photonic computing startup Lightmatter is taking its big shot at the rapidly growing AI computation market with a hardware-software combo it claims will help the industry level up — and save a lot of electricity to boot.

Lightmatter’s chips basically use optical flow to solve computational processes like matrix vector products. This math is at the heart of a lot of AI work and currently performed by GPUs and TPUs that specialize in it but use traditional silicon gates and transistors.

The issue with those is that we’re approaching the limits of density and therefore speed for a given wattage or size. Advances are still being made but at great cost and pushing the edges of classical physics. The supercomputers that make training models like GPT-4 possible are enormous, consume huge amounts of power and produce a lot of waste heat.

“The biggest companies in the world are hitting an energy power wall and experiencing massive challenges with AI scalability. Traditional chips push the boundaries of what’s possible to cool, and data centers produce increasingly large energy footprints. AI advances will slow significantly unless we deploy a new solution in data centers,” said Lightmatter CEO and founder Nick Harris.

“Some have projected that training a single large language model can take more energy than 100 U.S. homes consume in a year. Additionally, there are estimates that 10%-20% of the world’s total power will go to AI inference by the end of the decade unless new compute paradigms are created.”

Lightmatter, of course, intends to be one of those new paradigms. Its approach is, at least potentially, faster and more efficient, using arrays of microscopic optical waveguides to let the light essentially perform logic operations just by passing through them: a sort of analog-digital hybrid. Since the waveguides are passive, the main power draw is creating the light itself, then reading and handling the output.

One really interesting aspect of this form of optical computing is that you can increase the power of the chip just by using more than one color at once. Blue does one operation while red does another — though in practice it’s more like 800 nanometers wavelength does one, 820 does another. It’s not trivial to do so, of course, but these “virtual chips” can vastly increase the amount of computation done on the array. Twice the colors, twice the power.

Harris started the company based on optical computing work he and his team did at MIT (which is licensing the relevant patents to them) and managed to wrangle an $11 million seed round back in 2018. One investor said then that “this isn’t a science project,” but Harris admitted in 2021 that while they knew “in principle” the tech should work, there was a hell of a lot to do to make it operational. Fortunately, he was telling me that in the context of investors dropping a further $80 million on the company.

Now Lightmatter has raised a $154 million C round and is preparing for its actual debut. It has several pilots going with its full stack of Envise (computing hardware), Passage (interconnect, crucial for large computing operations) and Idiom, a software platform that Harris says should let machine learning developers adapt quickly.

A Lightmatter Envise unit in captivity. Image Credits: Lightmatter

“We’ve built a software stack that integrates seamlessly with PyTorch and TensorFlow. The workflow for machine learning developers is the same from there — we take the neural networks built in these industry standard applications and import our libraries, so all the code runs on Envise,” he explained.

The company declined to make any specific claims about speedups or efficiency improvements, and because it’s a different architecture and computing method it’s hard to make apples-to-apples comparisons. But we’re definitely talking along the lines of an order of magnitude, not a measly 10% or 15%. Interconnect is similarly upgraded, since it’s useless to have that level of processing isolated on one board.

Of course, this is not the kind of general-purpose chip that you could use in your laptop; it’s highly specific to this task. But it’s the lack of task specificity at this scale that seems to be holding back AI development — though “holding back” is the wrong term since it’s moving at great speed. But that development is hugely costly and unwieldy.

The pilots are in beta, and mass production is planned for 2024, at which point presumably they ought to have enough feedback and maturity to deploy in data centers.

The funding for this round came from SIP Global, Fidelity Management & Research Company, Viking Global Investors, GV, HPE Pathfinder and existing investors.

Lightmatter’s photonic AI hardware is ready to shine with $154M in new funding by Devin Coldewey originally published on TechCrunch

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Lightmatter’s photonic AI hardware is ready to shine with $154M in new funding

Photonic computing startup Lightmatter is taking its big shot at the rapidly growing AI computation market with a hardware-software combo it claims will help the industry level up — and save a lot of electricity to boot.

Lightmatter’s chips basically use optical flow to solve computational processes like matrix vector products. This math is at the heart of a lot of AI work and currently performed by GPUs and TPUs that specialize in it but use traditional silicon gates and transistors.

The issue with those is that we’re approaching the limits of density and therefore speed for a given wattage or size. Advances are still being made but at great cost and pushing the edges of classical physics. The supercomputers that make training models like GPT-4 possible are enormous, consume huge amounts of power and produce a lot of waste heat.

“The biggest companies in the world are hitting an energy power wall and experiencing massive challenges with AI scalability. Traditional chips push the boundaries of what’s possible to cool, and data centers produce increasingly large energy footprints. AI advances will slow significantly unless we deploy a new solution in data centers,” said Lightmatter CEO and founder Nick Harris.

“Some have projected that training a single large language model can take more energy than 100 U.S. homes consume in a year. Additionally, there are estimates that 10%-20% of the world’s total power will go to AI inference by the end of the decade unless new compute paradigms are created.”

Lightmatter, of course, intends to be one of those new paradigms. Its approach is, at least potentially, faster and more efficient, using arrays of microscopic optical waveguides to let the light essentially perform logic operations just by passing through them: a sort of analog-digital hybrid. Since the waveguides are passive, the main power draw is creating the light itself, then reading and handling the output.

One really interesting aspect of this form of optical computing is that you can increase the power of the chip just by using more than one color at once. Blue does one operation while red does another — though in practice it’s more like 800 nanometers wavelength does one, 820 does another. It’s not trivial to do so, of course, but these “virtual chips” can vastly increase the amount of computation done on the array. Twice the colors, twice the power.

Harris started the company based on optical computing work he and his team did at MIT (which is licensing the relevant patents to them) and managed to wrangle an $11 million seed round back in 2018. One investor said then that “this isn’t a science project,” but Harris admitted in 2021 that while they knew “in principle” the tech should work, there was a hell of a lot to do to make it operational. Fortunately, he was telling me that in the context of investors dropping a further $80 million on the company.

Now Lightmatter has raised a $154 million C round and is preparing for its actual debut. It has several pilots going with its full stack of Envise (computing hardware), Passage (interconnect, crucial for large computing operations) and Idiom, a software platform that Harris says should let machine learning developers adapt quickly.

A Lightmatter Envise unit in captivity. Image Credits: Lightmatter

“We’ve built a software stack that integrates seamlessly with PyTorch and TensorFlow. The workflow for machine learning developers is the same from there — we take the neural networks built in these industry standard applications and import our libraries, so all the code runs on Envise,” he explained.

The company declined to make any specific claims about speedups or efficiency improvements, and because it’s a different architecture and computing method it’s hard to make apples-to-apples comparisons. But we’re definitely talking along the lines of an order of magnitude, not a measly 10% or 15%. Interconnect is similarly upgraded, since it’s useless to have that level of processing isolated on one board.

Of course, this is not the kind of general-purpose chip that you could use in your laptop; it’s highly specific to this task. But it’s the lack of task specificity at this scale that seems to be holding back AI development — though “holding back” is the wrong term since it’s moving at great speed. But that development is hugely costly and unwieldy.

The pilots are in beta, and mass production is planned for 2024, at which point presumably they ought to have enough feedback and maturity to deploy in data centers.

The funding for this round came from SIP Global, Fidelity Management & Research Company, Viking Global Investors, GV, HPE Pathfinder and existing investors.

Lightmatter’s photonic AI hardware is ready to shine with $154M in new funding by Devin Coldewey originally published on TechCrunch

source https://techcrunch.com/2023/05/31/lightmatters-photonic-ai-hardware-is-ready-to-shine-with-154m-in-new-funding/

Amazon settles with FTC for $25M after ‘flouting’ kids’ privacy and deletion requests

Amazon will pay the FTC a $25 million penalty as well as “overhaul its deletion practices and implement stringent privacy safeguards” to avoid charges of violating the Children’s Online Privacy Protection Act to spruce up its AI.

Amazon’s voice interface Alexa has been in use in homes across the globe for years, and any parent who has one knows that kids love to play with it, make it tell jokes, even use it for its intended purpose, whatever that is. In fact it was so obviously useful to kids who can’t write or have disabilities that the FTC relaxed COPPA rules to accommodate reasonable usage: certain service-specific analysis of kids’ data, like transcription, was allowed as long as it is not retained any longer than reasonably necessary.

It seems that Amazon may have taken a rather expansive view on the “reasonably necessary” timescale, keeping kids’ speech data more or less forever. As the FTC puts it:

Amazon retained children’s recordings indefinitely—unless a parent requested that this information be deleted, according to the complaint. And even when a parent sought to delete that information, the FTC said, Amazon failed to delete transcripts of what kids said from all its databases.

Geolocation data was also not deleted, a problem the company “repeatedly failed to fix.”

This has been going on for years — the FTC alleges that Amazon knew about it as early as 2018 but didn’t take action until September of the next year, after the agency gave them a helpful nudge.

Alexa, does the Echo Dot Kids protect children’s privacy?

That kind of timing usually indicates that a company would have continued with this practice forever. And apparently, due to “faulty fixes and process fiascos,” some of those practices did continue until 2022!

You may well ask, what is the point of having a bunch of recordings of kids talking to Alexa? Well, if you plan on having your voice interface talk to kids a lot, it sure helps to have a secret database of audio interactions that you can train your machine learning models on. And that’s how the FTC said Amazon justified its retention of this data.

FTC Commissioners Bedoya and Slaughter, as well as Chair Khan, wrote a statement accompanying the settlement proposal and complaint to particularly call out this one point:

The Commission alleges that Amazon kept kids’ data indefinitely to further refine its voice recognition algorithm. Amazon is not alone in apparently seeking to amass data to refine its machine learning models; right now, with the advent of large language models, the tech industry as a whole is sprinting to do the same.

Today’s settlement sends a message to all those companies: Machine learning is no excuse to break the law. Claims from businesses that data must be indefinitely retained to improve algorithms do not override legal bans on indefinite retention of data. The data you use to improve your algorithms must be lawfully collected and lawfully retained. Companies would do well to heed this lesson.

And so today we have the $25 million fine, which is of course less than negligible for a company Amazon’s size. It’s clearly complying with the other provisions of the proposed order that will likely give them a headache. The FTC says the order would:

• Prohibit Amazon from using geolocation, voice information, and children’s voice information subject to consumers’ deletion requests for the creation or improvement of any data product;
• Require the company to delete inactive Alexa accounts of children;
• Require Amazon to notify users about the FTC-DOJ action against the company;
• Require Amazon to notify users of its retention and deletion practices and controls;
• Prohibit Amazon from misrepresenting its privacy policies related to geolocation, voice and children’s voice information; and
• Mandate the creation and implementation of a privacy program related to the company’s use of geolocation information.

This settlement and action is totally independent from the FTC’s other one announced today, with Amazon subsidiary Ring. There is a certain common thread of “failing to implement basic privacy and security protections,” though.

In a statement, Amazon said that “While we disagree with the FTC’s claims and deny violating the law, this settlement puts the matter behind us.” They also promise to “remove child profiles that have been inactive for more than 18 months,” which seems incredibly long to retain that data. I’ve followed up with questions about that duration and whether the data will be used for ML training, and will update if I hear back.

Amazon settles with FTC for $25M after ‘flouting’ kids’ privacy and deletion requests by Devin Coldewey originally published on TechCrunch

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Amazon settles with FTC for $25M after ‘flouting’ kids’ privacy and deletion requests

Amazon will pay the FTC a $25 million penalty as well as “overhaul its deletion practices and implement stringent privacy safeguards” to avoid charges of violating the Children’s Online Privacy Protection Act to spruce up its AI.

Amazon’s voice interface Alexa has been in use in homes across the globe for years, and any parent who has one knows that kids love to play with it, make it tell jokes, even use it for its intended purpose, whatever that is. In fact it was so obviously useful to kids who can’t write or have disabilities that the FTC relaxed COPPA rules to accommodate reasonable usage: certain service-specific analysis of kids’ data, like transcription, was allowed as long as it is not retained any longer than reasonably necessary.

It seems that Amazon may have taken a rather expansive view on the “reasonably necessary” timescale, keeping kids’ speech data more or less forever. As the FTC puts it:

Amazon retained children’s recordings indefinitely—unless a parent requested that this information be deleted, according to the complaint. And even when a parent sought to delete that information, the FTC said, Amazon failed to delete transcripts of what kids said from all its databases.

Geolocation data was also not deleted, a problem the company “repeatedly failed to fix.”

This has been going on for years — the FTC alleges that Amazon knew about it as early as 2018 but didn’t take action until September of the next year, after the agency gave them a helpful nudge.

Alexa, does the Echo Dot Kids protect children’s privacy?

That kind of timing usually indicates that a company would have continued with this practice forever. And apparently, due to “faulty fixes and process fiascos,” some of those practices did continue until 2022!

You may well ask, what is the point of having a bunch of recordings of kids talking to Alexa? Well, if you plan on having your voice interface talk to kids a lot, it sure helps to have a secret database of audio interactions that you can train your machine learning models on. And that’s how the FTC said Amazon justified its retention of this data.

FTC Commissioners Bedoya and Slaughter, as well as Chair Khan, wrote a statement accompanying the settlement proposal and complaint to particularly call out this one point:

The Commission alleges that Amazon kept kids’ data indefinitely to further refine its voice recognition algorithm. Amazon is not alone in apparently seeking to amass data to refine its machine learning models; right now, with the advent of large language models, the tech industry as a whole is sprinting to do the same.

Today’s settlement sends a message to all those companies: Machine learning is no excuse to break the law. Claims from businesses that data must be indefinitely retained to improve algorithms do not override legal bans on indefinite retention of data. The data you use to improve your algorithms must be lawfully collected and lawfully retained. Companies would do well to heed this lesson.

And so today we have the $25 million fine, which is of course less than negligible for a company Amazon’s size. It’s clearly complying with the other provisions of the proposed order that will likely give them a headache. The FTC says the order would:

• Prohibit Amazon from using geolocation, voice information, and children’s voice information subject to consumers’ deletion requests for the creation or improvement of any data product;
• Require the company to delete inactive Alexa accounts of children;
• Require Amazon to notify users about the FTC-DOJ action against the company;
• Require Amazon to notify users of its retention and deletion practices and controls;
• Prohibit Amazon from misrepresenting its privacy policies related to geolocation, voice and children’s voice information; and
• Mandate the creation and implementation of a privacy program related to the company’s use of geolocation information.

This settlement and action is totally independent from the FTC’s other one announced today, with Amazon subsidiary Ring. There is a certain common thread of “failing to implement basic privacy and security protections,” though.

I’ve asked Amazon for comment on the settlement and will update this post if I hear back.

Amazon settles with FTC for $25M after ‘flouting’ kids’ privacy and deletion requests by Devin Coldewey originally published on TechCrunch

source https://techcrunch.com/2023/05/31/amazon-settles-with-ftc-for-25m-after-flouting-kids-privacy-and-deletion-requests/

No ChatGPT in my court: Judge orders all AI-generated content must be declared and checked

Few lawyers would be foolish enough to let an AI make their arguments, but one already did, and Judge Brantley Starr is taking steps to ensure that debacle isn’t repeated in his courtroom.

The Texas federal judge has added a requirement that any attorney appearing in his court must attest that “no portion of the filing was drafted by generative artificial intelligence,” or if it was, that it was checked “by a human being.”

Last week, attorney Steven Schwartz allowed ChatGPT to “supplement” his legal research in a recent federal filing, providing him with six cases and relevant precedent — all of which were completely hallucinated by the language model. He now “greatly regrets” doing this, and while the national coverage of this gaffe probably caused any other lawyers thinking of trying it to think again, Judge Starr isn’t taking any chances.

At the federal site for Texas’s Northern District, Starr has, like other judges, the opportunity to set specific rules for his courtroom. And added recently (though it’s unclear whether this was in response to the aforementioned filing) is the “Mandatory Certification Regarding Generative Artificial Intelligence.” Eugene Volokh first reported the news.

All attorneys appearing before the Court must file on the docket a certificate attesting either that no portion of the filing was drafted by generative artificial intelligence (such as ChatGPT, Harvey.AI, or Google Bard) or that any language drafted by generative artificial intelligence was checked for accuracy, using print reporters or traditional legal databases, by a human being.

A form for lawyers to sign is appended, noting that “quotations, citations, paraphrased assertions, and legal analysis” are all covered by this proscription. As summary is one of AI’s strong suits, and finding and summarizing precedent or previous cases is something that has been advertised as potentially helpful in legal work, this may end up coming into play more often than expected.

Whoever drafted the memorandum on this matter at Judge Starr’s office has their finger on the pulse. The certification requirement includes a pretty well informed and convincing explanation of its necessity (line breaks added for readability):

These platforms are incredibly powerful and have many uses in the law: form divorces, discovery requests, suggested errors in documents, anticipated questions at oral argument. But legal briefing is not one of them. Here’s why.

These platforms in their current states are prone to hallucinations and bias. On hallucinations, they make stuff up—even quotes and citations. Another issue is reliability or bias. While attorneys swear an oath to set aside their personal prejudices, biases, and beliefs to faithfully uphold the law and represent their clients, generative artificial intelligence is the product of programming devised by humans who did not have to swear such an oath.

As such, these systems hold no allegiance to any client, the rule of law, or the laws and Constitution of the United States (or, as addressed above, the truth). Unbound by any sense of duty, honor, or justice, such programs act according to computer code rather than conviction, based on programming rather than principle. Any party believing a platform has the requisite accuracy and reliability for legal briefing may move for leave and explain why.

In other words, be prepared to justify yourself.

While this is just one judge in one court, it would not be surprising if others took up this rule as their own. While as the court says, this is a powerful and potentially helpful technology, its use must be at the very least clearly declared and checked for accuracy.

No ChatGPT in my court: Judge orders all AI-generated content must be declared and checked by Devin Coldewey originally published on TechCrunch

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Elizabeth Holmes is now behind bars: How we got here

Ten years ago, Elizabeth Holmes’ biotech startup, Theranos, was valued to be worth $10 billion. Five years ago, she was indicted for wire fraud. Finally, today, Holmes reported to prison to begin serving her sentence of 11 years and 3 months.

It usually doesn’t take so long after an indictment for a defendant to be found guilty and sent to prison. But the fall of the woman formerly hailed as the next Steve Jobs has been painfully drawn out, with Holmes’ legal team playing every card in the deck to delay this inevitable day.

The story of Theranos is all too familiar now: A young Stanford dropout set out to revolutionize healthcare with cutting-edge blood testing technology, scored high-profile investors and fawning press coverage, but it all came crashing down in 2015, when Wall Street Journal reporter John Carreyrou revealed that Theranos’ technology didn’t actually work. To make matters worse, unsuspecting patients were getting blood tests on Theranos machines, endangering their health with false positives for conditions like cancer, HIV and even a miscarriage.

Since then, the unraveling of the now-infamous blood testing startup has been a long, messy process. Hopefully, this is the last Theranos-related coverage that will appear for a while, with both Holmes and co-conspirator Sunny Balwani behind bars. So, if you’re looking to catch up on what’s been happening since Theranos was exposed for its dangerous medical practices, go forth and read.

Lawsuits, layoffs abound (2016-2017)

Once investors realized that Theranos was all smoke and mirrors, things got real litigious real quick. The U.S. government began its investigation of Theranos in 2016, and over the two years that followed, Theranos continued making headlines, but they were no longer so complimentary.

• Ex-Theranos customer files a lawsuit claiming faulty blood tests contributed to his heart attack (July 2016)
• Theranos closes its labs and wellness centers, lays off 340 (October 2016)
• A hedge fund is now suing Theranos, citing “lies, material misstatements, and omissions” (October 2016)
• Walgreens is now suing Theranos for $140 million in Delaware (November 2016)
• A prominent Silicon Valley investment banker is suing Theranos, and seeking class-action status (November 2016)
• Theranos slashes another 41% of its workforce (January 2017)
• Arizona plans to sue Theranos over faulty blood tests (January 2017)
• Theranos closed its last remaining blood-testing lab after it reportedly failed an inspection (January 2017)
• Theranos is offering investors Elizabeth Holmes’ shares if they promise not to sue (March 2017)
• Theranos gets $100 million in debt financing to carry it through 2018, with some caveats (December 2017)

The dissolution of Theranos (2018)

Looking back at those two years of headlines, it’s a wonder that Theranos even made it to 2018. Finally, the company dissolved, and Holmes and Balwani were officially charged with fraud by the U.S. government.

• Theranos founder Elizabeth Holmes charged with massive, ‘years-long fraud’ (March 2018)
• Theranos reportedly lays off most of its remaining employees as it tries to avoid bankruptcy (April 2018)
• Elizabeth Holmes reportedly steps down at Theranos after criminal indictment (June 2018)
• WSJ reports that Theranos will finally dissolve (September 2018)

Theranos’ downfall became not just a major story in tech, but a fascination of Hollywood. Within months of the company’s end, a documentary about Theranos screened at Sundance, ABC greenlit a documentary and podcast, and Hulu ordered the mini-series that would become “The Dropout.” Apple was working on a Theranos movie starring Jennifer Lawrence, but after seeing “The Dropout,” Lawrence felt like there wasn’t much more to add and left the project.

Sunny Balwani (Naveen Andrews) and Elizabeth Holmes (Amanda Seyfried). (Photo by: Beth Dubber/Hulu)

Elizabeth Holmes and Sunny Balwani go to trial (2021-2023)

Holmes and Balwani were supposed to be tried for fraud in June 2020, but the trial was pushed back due to the coronavirus pandemic. Then, Holmes became pregnant with her first child, further delaying the trial. Though the two executives were supposed to be tried together, Holmes’ legal team successfully moved for separate trials, alleging that Balwani had abused Holmes while they had been secretly dating for several years. Holmes would later testify about how this abuse impacted her actions as CEO of Theranos, but ultimately, the jury was not litigating the relationship between Holmes and her COO. After a long deliberation, Holmes was found guilty on 4 out of 11 counts of defrauding and conspiring to defraud investors, but she was found not-guilty of any charges related to defrauding patients. At Balwani’s trial, which took place months later, he was found guilty on all counts.

• Theranos founder Elizabeth Holmes testifies in her own criminal trial (November 2021)
• Elizabeth Holmes convicted of 4 of 11 fraud counts in Theranos trial (January 2022)
• Former Theranos exec Sunny Balwani is found guilty of fraud (July 2022)
• Elizabeth Holmes sentenced to 11 years in prison for Theranos fraud (November 2022)
• Theranos exec Sunny Balwani sentenced to 13 years in prison for defrauding patients and investors (December 2022)
• Elizabeth Holmes is denied request to stay out of prison (April 2023)
• Theranos founder Elizabeth Holmes isn’t headed to jail tomorrow after all (April 2023)
• Time’s up for Elizabeth Holmes (May 2023)

Aftermath

What can we still learn from one of the most infamous startup implosions of all time? Well, don’t do fraud. But also, we have some other ideas. Here are our takes on what Theranos says about the tech industry at large, and how it figures into the history of Silicon Valley.

• How the myth of the ‘girlboss’ harms emerging women in tech
• Elizabeth Holmes, left to her own devices
• Holmes’ sentencing sends a clear message that the startup ecosystem must be built on good faith
• What’s left to learn from Theranos? Have friends.
• The Theranos fiasco shows how much startup advisory boards matter
• I get it, Elizabeth Holmes
• The next Theranos should be shortable

Elizabeth Holmes, left to her own devices

What’s left to learn from Theranos? Have friends.

Elizabeth Holmes is now behind bars: How we got here by Amanda Silberling originally published on TechCrunch

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via IFTTT

Elizabeth Holmes is now behind bars: How we got here

Ten years ago, Elizabeth Holmes’ biotech startup, Theranos, was valued to be worth $10 billion. Five years ago, she was indicted for wire fraud. Finally, today, Holmes reported to prison to begin serving her sentence of 11 years and 3 months.

It usually doesn’t take so long after an indictment for a defendant to be found guilty and sent to prison. But the fall of the woman formerly hailed as the next Steve Jobs has been painfully drawn out, with Holmes’ legal team playing every card in the deck to delay this inevitable day.

The story of Theranos is all too familiar now: A young Stanford dropout set out to revolutionize healthcare with cutting-edge blood testing technology, scored high-profile investors and fawning press coverage, but it all came crashing down in 2015, when Wall Street Journal reporter John Carreyrou revealed that Theranos’ technology didn’t actually work. To make matters worse, unsuspecting patients were getting blood tests on Theranos machines, endangering their health with false positives for conditions like cancer, HIV and even a miscarriage.

Since then, the unraveling of the now-infamous blood testing startup has been a long, messy process. Hopefully, this is the last Theranos-related coverage that will appear for a while, with both Holmes and co-conspirator Sunny Balwani behind bars. So, if you’re looking to catch up on what’s been happening since Theranos was exposed for its dangerous medical practices, go forth and read.

Lawsuits, layoffs abound (2016-2017)

Once investors realized that Theranos was all smoke and mirrors, things got real litigious real quick. The U.S. government began its investigation of Theranos in 2016, and over the two years that followed, Theranos continued making headlines, but they were no longer so complimentary.

• Ex-Theranos customer files a lawsuit claiming faulty blood tests contributed to his heart attack (July 2016)
• Theranos closes its labs and wellness centers, lays off 340 (October 2016)
• A hedge fund is now suing Theranos, citing “lies, material misstatements, and omissions” (October 2016)
• Walgreens is now suing Theranos for $140 million in Delaware (November 2016)
• A prominent Silicon Valley investment banker is suing Theranos, and seeking class-action status (November 2016)
• Theranos slashes another 41% of its workforce (January 2017)
• Arizona plans to sue Theranos over faulty blood tests (January 2017)
• Theranos closed its last remaining blood-testing lab after it reportedly failed an inspection (January 2017)
• Theranos is offering investors Elizabeth Holmes’ shares if they promise not to sue (March 2017)
• Theranos gets $100 million in debt financing to carry it through 2018, with some caveats (December 2017)

The dissolution of Theranos (2018)

Looking back at those two years of headlines, it’s a wonder that Theranos even made it to 2018. Finally, the company dissolved, and Holmes and Balwani were officially charged with fraud by the U.S. government.

• Theranos founder Elizabeth Holmes charged with massive, ‘years-long fraud’ (March 2018)
• Theranos reportedly lays off most of its remaining employees as it tries to avoid bankruptcy (April 2018)
• Elizabeth Holmes reportedly steps down at Theranos after criminal indictment (June 2018)
• WSJ reports that Theranos will finally dissolve (September 2018)

Theranos’ downfall became not just a major story in tech, but a fascination of Hollywood. Within months of the company’s end, a documentary about Theranos screened at Sundance, ABC greenlit a documentary and podcast, and Hulu ordered the mini-series that would become “The Dropout.” Apple was working on a Theranos movie starring Jennifer Lawrence, but after seeing “The Dropout,” Lawrence felt like there wasn’t much more to add and left the project.

Sunny Balwani (Naveen Andrews) and Elizabeth Holmes (Amanda Seyfried). (Photo by: Beth Dubber/Hulu)

Elizabeth Holmes and Sunny Balwani go to trial (2021-2023)

Holmes and Balwani were supposed to be tried for fraud in June 2020, but the trial was pushed back due to the coronavirus pandemic. Then, Holmes became pregnant with her first child, further delaying the trial. Though the two executives were supposed to be tried together, Holmes’ legal team successfully moved for separate trials, alleging that Balwani had abused Holmes while they had been secretly dating for several years. Holmes would later testify about how this abuse impacted her actions as CEO of Theranos, but ultimately, the jury was not litigating the relationship between Holmes and her COO. After a long deliberation, Holmes was found guilty on 4 out of 11 counts of defrauding and conspiring to defraud investors, but she was found not-guilty of any charges related to defrauding patients. At Balwani’s trial, which took place months later, he was found guilty on all counts.

• Theranos founder Elizabeth Holmes testifies in her own criminal trial (November 2021)
• Elizabeth Holmes convicted of 4 of 11 fraud counts in Theranos trial (January 2022)
• Former Theranos exec Sunny Balwani is found guilty of fraud (July 2022)
• Elizabeth Holmes sentenced to 11 years in prison for Theranos fraud (November 2022)
• Theranos exec Sunny Balwani sentenced to 13 years in prison for defrauding patients and investors (December 2022)
• Elizabeth Holmes is denied request to stay out of prison (April 2023)
• Theranos founder Elizabeth Holmes isn’t headed to jail tomorrow after all (April 2023)
• Time’s up for Elizabeth Holmes (May 2023)

Aftermath

What can we still learn from one of the most infamous startup implosions of all time? Well, don’t do fraud. But also, we have some other ideas. Here are our takes on what Theranos says about the tech industry at large, and how it figures into the history of Silicon Valley.

• How the myth of the ‘girlboss’ harms emerging women in tech
• Elizabeth Holmes, left to her own devices
• Holmes’ sentencing sends a clear message that the startup ecosystem must be built on good faith
• What’s left to learn from Theranos? Have friends.
• The Theranos fiasco shows how much startup advisory boards matter
• I get it, Elizabeth Holmes
• The next Theranos should be shortable

Elizabeth Holmes, left to her own devices

What’s left to learn from Theranos? Have friends.

Elizabeth Holmes is now behind bars: How we got here by Amanda Silberling originally published on TechCrunch

source https://techcrunch.com/2023/05/30/elizabeth-holmes-is-now-behind-bars-how-we-got-here/

Blackrock, a minority investor in Byju’s, cuts startup valuation to $8.4 billion

Blackrock, a minority investor in Byju’s, has yet again cut the valuation of its holding in the Bengaluru-based startup, this time to about $8.4 billion, even as the most Indian valuable startup continues to raise capital at a better price.

Blackrock cut the value of Byju’s share by 62% in the quarter ending March this year, from a year ago, it disclosed in a filing.

Nonetheless, a series of qualifications merit attention: Blackrock is not a substantial stakeholder in Byju’s, and owns less than 1% equity in the startup.

A similar move from Prosus, one of the more prominent investors in Byju’s, would have raised greater alarms for the Indian edtech leader. Additionally, it’s worth noting that valuation methodologies may vary across different investors. Thus, other portfolio investors could potentially hold vastly contrasting views.

Furthermore, Byju’s recently secured a $250 million in fresh funding at a valuation cap of $22 billion earlier this month, indicating that the startup continues to be valued higher by other backers.

Blackrock’s price adjustment is the latest in a series of valuation markdowns for the Indian startup ecosystem. Invesco has cut the valuation of Swiggy by half, and Pine Labs and Pharmeasy have also seen their values being cut by some investors.

Blackrock, a minority investor in Byju’s, cuts startup valuation to $8.4 billion by Manish Singh originally published on TechCrunch

source https://techcrunch.com/2023/05/30/blackrock-a-minority-investor-in-byjus-cuts-startup-valuation-to-8-4-billion/

Amazon is testing dine-in payments in India

After shutting down its food delivery business last year, Amazon India is now experimenting with dine-in payments. The company has initiated a limited introduction of bill payments at restaurants using Amazon Pay.

The facility is currently active in select areas of Bengaluru with a limited set of restaurants. Users can head to Amazon Pay > Dining in the Amazon app to make payments using credit/debit cards, net banking, UPI, or Amazon Pay Later. At the moment, Amazon India is offering discounts on bill payments at almost all listed restaurants.

Image Credits: Amazon

It’s not clear if the e-commerce group is testing this in any other city. Amazon India spokespeople did not respond to a request for comment.

Image Credits: Amazon

Food delivery bigwigs Zomato and Swiggy both offer in-restaurant payments and discounts as they attempt to attract more customers. Earlier this month, Zomato launched its own UPI service in partnership with the ICICI bank for quicker checkout and bill payment.

The National Restaurant Association of India, a consortium in the hospitality sector, last year warned against dining payment products from food delivery firms in an advisory to its members.

Amazon’s new experiment is another attempt at finding ways to engage customers in India. It is facing challenges in India and has struggled to make inroads into smaller towns in the country, according to a report from investment firm Sanford C. Bernstein. The e-commerce giant insists that 85% of its customers are from tier 2/3 cities/towns.

Bernstein’s report also noted that the company is facing a tough regulatory environment and as a result falling behind Walmart-backed Flipkart. Notably, Amazon omitted India mentions for the first time since 2014 from its Q1 2023 results.

Earlier this year, Amazon joined Open Network for Digital Commerce, an initiative set up by India’s ecommerce ministry, in limited capacity to create an “interoperable” network for sellers. ONCD’s aim is to let retailers join a digital network that doesn’t rely on central marketplaces like Amazon and Flipkart.

India warns e-commerce giants, urges adoption of open network

Amazon is testing dine-in payments in India by Ivan Mehta originally published on TechCrunch

from TechCrunch https://ift.tt/9YKA47j
via IFTTT

Amazon is testing dine-in payments in India

After shutting down its food delivery business last year, Amazon India is now experimenting with dine-in payments. The company has initiated a limited introduction of bill payments at restaurants using Amazon Pay.

The facility is currently active in select areas of Bengaluru with a limited set of restaurants. Users can head to Amazon Pay > Dining in the Amazon app to make payments using credit/debit cards, net banking, UPI, or Amazon Pay Later. At the moment, Amazon India is offering discounts on bill payments at almost all listed restaurants.

Image Credits: Amazon

It’s not clear if the e-commerce group is testing this in any other city. Amazon India spokespeople did not respond to a request for comment.

Image Credits: Amazon

Food delivery bigwigs Zomato and Swiggy both offer in-restaurant payments and discounts as they attempt to attract more customers. Earlier this month, Zomato launched its own UPI service in partnership with the ICICI bank for quicker checkout and bill payment.

The National Restaurant Association of India, a consortium in the hospitality sector, last year warned against dining payment products from food delivery firms in an advisory to its members.

Amazon’s new experiment is another attempt at finding ways to engage customers in India. It is facing challenges in India and has struggled to make inroads into smaller towns in the country, according to a report from investment firm Sanford C. Bernstein. The e-commerce giant insists that 85% of its customers are from tier 2/3 cities/towns.

Bernstein’s report also noted that the company is facing a tough regulatory environment and as a result falling behind Walmart-backed Flipkart. Notably, Amazon omitted India mentions for the first time since 2014 from its Q1 2023 results.

Earlier this year, Amazon joined Open Network for Digital Commerce, an initiative set up by India’s ecommerce ministry, in limited capacity to create an “interoperable” network for sellers. ONCD’s aim is to let retailers join a digital network that doesn’t rely on central marketplaces like Amazon and Flipkart.

India warns e-commerce giants, urges adoption of open network

Amazon is testing dine-in payments in India by Ivan Mehta originally published on TechCrunch

source https://techcrunch.com/2023/05/30/amazon-is-testing-dine-in-payments-in-india/

Max Q: Galactic

Hello and welcome back to Max Q! Happy Memorial Day everyone.

In this issue:

• Astranis’ novel approach to GEO satellites
• Virgin Galactic’s return to the skies
• News from SpaceX, and more

Astranis’ novel approach to internet satellites is starting to pay off

Astranis, a satellite internet startup based in San Francisco, said Wednesday that its first spacecraft completed a milestone test and will start bringing broadband access to rural Alaskans as soon as mid-June.

It’s a major step for the company, which was founded in 2015 by John Gedmark and Ryan McLinko. By taking a first principles approach to satellite development, the pair bet that they could make a smaller, cheaper spacecraft for geosynchronous orbit — the orbit farthest from Earth and arguably the most inhospitable — and use them to bring internet to millions, or even billions, of people around the globe.

Their bet is paying off: The company’s first satellite, Arcturus, launched on a Falcon Heavy at the end of April. Within less than two minutes after separating from the rocket’s upper stage, the spacecraft started sending telemetry and tracking data to Astranis engineers. From there, the satellite connected to an internet gateway in Utah and communicated with multiple user terminals in Alaska for the first time.

Image Credits: Astranis

Following successful mission, Virgin Galactic targeting June for first commercial spaceflight

Following a successful flight to the edge of space, space tourism company Virgin Galactic says it is ready to enter commercial service in June.

Virgin Galactic’s aircraft, VMS Eve, departed the New Mexico launch site carrying a crew of six (plus two aircraft pilots) at around 9:15 a.m. MT. The VSS Unity spaceplane dropped from the wing of the jet a little over an hour later, taking off to suborbital space at an altitude of 44,500 feet. The entire mission lasted around 90 minutes.

The mission, called Unity 25, concludes a nearly two-year pause in operations for the company. That last flight, which took place in June 2021, also took six people to suborbital space, including company founder billionaire Richard Branson. While Virgin Galactic did not broadcast the Unity 25 mission, the company kept followers updated on social media. NASA Spaceflight, a private news website with massive followings on YouTube and Twitter, unofficially livestreamed the flight.

Image Credits: Virgin Galactic

More news from TC and beyond

• Fleet Space raised $33 million to grow its space-based mineral prospecting business. (SpaceNews)
• Gitai, a Tokyo-based startup, wants to use robots as the labor force for the moon and Mars. (TechCrunch)
• NASA is still working on construction of Mobile Launcher 2 for the next Space Launch System mission (Artemis II), with steel arriving at Kennedy Space Center. (Bechtel)
• NASA’s Office of the Inspector General found dismaying cost overruns with the Artemis program, and in particular the development of the Space Launch System and the RS-25 rocket engines. (OIG)
• Satellite Vu, a thermal imaging startup, closed a new tranche of funding ahead of its first launch. (TechCrunch)
• SpaceX will join the U.S. Federal Aviation Administration as a co-defendant in a lawsuit filed against the regulator over environmental effects of the Starship launch program. (CNBC)
• South Korea launched a domestically built rocket to space. (Reuters)
• SkyFi lets anyone order satellite imagery from their smartphone. (TechCrunch)
• The Spaceport Company demonstrated the potential for off-shore rocket launches in partnership with Evolution Space. (Evolution)
• TRL11 closed pre-seed funding to further develop video solutions for the space environment. (TRL11)
• Ursa Major won a contract with the U.S. Air Force to continue the development of two massive engines, one for space launch and one for hypersonics. (DefenseNews)
• Virgin Orbit’s launch business was sold for parts to Rocket Lab, Stratolaunch and Vast. (TechCrunch)

 

Max Q is brought to you by me, Aria Alamalhodaei. If you enjoy reading Max Q, consider forwarding it to a friend. 

Max Q: Galactic by Aria Alamalhodaei originally published on TechCrunch

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