A hopeful entrant in the emerging market of electric watercraft is out of action and being sold for parts.
Pure Watercraft was founded in 2011 with the intention of replacing gas-based outboard motors with fully electric ones. We covered the company in 2016 when it began taking preorders for its first commercial outboards, and in 2020 Pure raised $23 million to step up production. GM even took a 25% stake in Pure as part of its big investment in electric infrastructure.
The company offered a electric outboard and battery combo that could be mounted on a boat like any other outboard, or in a package with a rigid inflatable or pontoon boat. With prices ranging from $21,600 for just propulsion to nearly $100,000 for a full boat, Pure’s products were arguably no more affordable up front than gas options, but they were certainly a lot cleaner and quieter.
But a tough market seems to have put an end to Pure’s ambitions. The company entered receivership — a sort of alternative form of bankruptcy — in July, per filing documents in King County, Washington, where it is based. In August it was also reported that a planned multi-million-dollar factory in West Virginia would not be going forward.
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The documents describe numerous creditors, from individual investors to banks to the big one, GM, which put approximately $35 million into the venture. That wasn’t all cash, though: listed among Pure’s assets is some $25 million worth of “manufacturing support,” “know-how,” licensing of the name, and other forms of non-pecuniary goods. (This type of in-kind investment is fairly commonplace.)
On the asset side, we find $3.6 million in “finished goods,” likely the assembled motors and battery units built by Pure, though why those would not have gone out to the more than 900 people who paid a down payment is unclear (nor is whether refunds will be issued). Another $25.5 million of “raw materials” is also listed, but what this may be is unclear — other documents detailing sale of assets like boats and batteries don’t come near that sum.
TechCrunch has asked both Pure and GM for comment on the matter. GM did not offer a substantive response and we have not yet heard back from Pure.
Electric watercraft is a growing but still nascent industry, with startups like Candela, Navier, FleetZero and Zin Boats making a play for cleaner, more efficient waterways and infrastructure.
Now, X’s lawyers said the company had done exactly what Mr. Musk vowed not to: take down accounts that a Brazilian justice ordered removed because the judge said they threatened Brazil’s democracy. X also complied with the justice’s other demands, including paying fines and naming a new formal representative in the country, the lawyers said.
Strands is the NYT’s latest word game after the likes of Wordle, Spelling Bee and Connections – and it’s great fun. It can be difficult, though, so read on for my Strands hints.
SPOILER WARNING: Information about NYT Strands today is below, so don’t read on if you don’t want to know the answers.
Your Strands expert
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Your Strands expert
Marc McLaren
NYT Strands today (game #203) – hint #1 – today’s theme
What is the theme of today’s NYT Strands?
• Today’s NYT Strands theme is… I’ve got you under my skin
NYT Strands today (game #203) – hint #2 – clue words
Play any of these words to unlock the in-game hints system.
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TRAIN
THEM
RIVER
ROLE
HATE
HATER
NYT Strands today (game #203) – hint #3 – spangram
What is a hint for today’s spangram?
• They keep you going
NYT Strands today (game #203) – hint #4 – spangram position
What are two sides of the board that today’s spangram touches?
First: left, 5th row
Last: right, 5th row
Right, the answers are below, so DO NOT SCROLL ANY FURTHER IF YOU DON’T WANT TO SEE THEM.
NYT Strands today (game #203) – the answers
(Image credit: New York Times)
The answers to today’s Strands, game #203, are…
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BRAIN
LIVER
HEART
KIDNEYS
STOMACH
LUNGS
SPANGRAM: INTERNALORGANS
My rating: Easy
My score: Perfect
As is so often the case with Strands, the key today was in working out what the theme was, because once you had that the answers were all pretty obvious. The theme clue of ‘I’ve got you under my skin’ was a nice one – cryptic, but not to the extent that you didn’t have any idea what kind of thing you could be looking for. I found BRAIN by accident, and that was enough to make it clear what the other solutions would be. Finding the likes of KIDNEYS and LIVER was easy enough, and once the spangram was in place there was very little room for failure.
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Yesterday’s NYT Strands answers (Saturday 21 September, game #202)
ARENA
STADIUM
NIGHTCLUB
THEATER
FESTIVAL
SPANGRAM: CONCERTVENUE
What is NYT Strands?
Strands is the NYT’s new word game, following Wordle and Connections. It’s now out of beta so is a fully fledged member of the NYT’s games stable and can be played on the NYT Games site on desktop or mobile.
I’ve got a full guide to how to play NYT Strands, complete with tips for solving it, so check that out if you’re struggling to beat it each day.
Amazon’s Echo Show 15 smart assistant records audio and images in people’s homes
MICHAEL SIMON/startraksphoto.com/Cover Images
Police can access a trove of data from smart speakers found at crime scenes that could be invaluable in solving murders or burglaries, say researchers. Data on recently recognised faces, internet searches and any voice commands received could be extracted even without the owner’s permission or assistance from the manufacturer.
Jona Crasselt and Gaston Pugliese at the University of Erlangen-Nuremberg in Germany decided to explore how much information can be pulled from these devices after seeing news coverage of Amazon refusing to…
These days, when it comes to streaming services, you have your pick of options. Plenty of these come with a hefty price tag, and the major streamers regularly announce price hikes. However, consumers are feeling stretched thin and looking for ways to watch TV without breaking their budget in the process. That’s where advertising video on demand (AVOD) and free ad-supported streaming television (FAST) services come in. Options like Tubi, Pluto, the Roku Channel, and, more recently, Google TV are there to fill in the gap.
Tubi is one of the big players in this space, as an AVOD/FAST (we’ll refer to it as just free streaming going forward) service with more than 200,000 movies and TV shows and over 200 live TV channels — for free.
But just because it’s free doesn’t mean you should jump ship from all of your other streaming services. After all, can this Fox-owned free streaming platform really compete with the likes of Netflix, Hulu, and others? Here’s everything you need to know about Tubi.
Tubi is a streaming service with a twist: it’s free. The fast-growing company offers up a combination of on-demand movies and TV shows, originals (this would be the AVOD part), and live TV streaming channels (the FAST part) without you having to shell out for a monthly subscription. Think of it as a sort of commercialized version of Netflix without the subscription fees.
Since Tubi is free, you’re going to have to make some compromises, though. First and foremost, there are ads. They aren’t overwhelming, but they’re there. Second, the on-demand content is mostly older movies and shows rerun on cable and other broadcast services. However, while Tubi has yet to produce any of its own original content, the streamer has a ton of it made for the service that can be found in its Tubi Originals section. More on that below.
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Tubi was bought by Fox in 2020 for $440 million, and recently reported more than 81 million monthly active users as of September 2024.
Don’t be fooled: There’s plenty to watch on Tubi — it boasts the largest catalog of film and TV titles of any AVOD service at 200,000, and offers more than 200 live TV channels for local news and sports. The free streamer also has more than 100 original titles with more on the way this year, spanning several genres including thriller, sci-fi, horror, romance, adult animation, and Black cinema titles. It’s also bringing in some original content from its siblings TMZ, MarVista Entertainment, and animated specialist Bento Box Entertainment.
In the meantime, sift through Tubi and you’ll find several diamonds in the rough. A quick five-minute search unearthed several decent selections, including Lovecraft Country, Boondock Saints, Ready or Not, The Witches of Eastwick, Independence Day, Vice, and the docuseries How It’s Made. Tubi also offers live TV channels across entertainment, news, sports, and more, including ABC News, NBC News Now, Fox, TMZ, People TV, the NFL Channel, Fox Sports, and MLB. There’s also a fairly impressive offering of shows and movies on Tubi Kids, including The Secret Life of Pets, The Dark Crystal, The Magic Schoolbus, Transformers: Prime,Strawberry Shortcake, and more.
The catalog isn’t available in 4K Ultra HD resolution and tops out at Full HD, depending on the age of the material. There’s no option to upgrade for a better viewing experience, either. Tubi is free, so if you aren’t happy with the experience as is, you will need to seek out an alternative. Fortunately, there’s no shortage of them.
Chances are that if you own a (modern) device that can connect to the internet, it supports Tubi. The streaming service is accessible via your web browser and as a mobile app for both Android and iOS. It’s also available on streaming devices and systems such as Apple TV, Roku, Amazon Fire TV, Google Chromecast, Android TV, TiVo, and as we mentioned above, it was recently added to Google TV. There are even dedicated apps for the PlayStation 4 and Playstation 5, as well as Xbox One, Series X, and Series S.
If you don’t own a set-top box or streaming stick, you may be able to install it on your television itself. If you’re a Comcast Xfinity X1 or Cox Contour cable customer, you can add it to your plan. Plus, owners of Samsung, Sony, Vizio, Hisense, or LG smart TVs can find the Tubi application available in their respective app store. If you’re outside the U.S., however, the list of supported devices varies from country to country.
Given the nonexistent price, there isn’t a whole lot to Tubi when it comes to features. If you want to watch something aimed at mature audiences, you’ll need to register for an account — and that’s where the tools come in. Doing so will allow you to continue watching where you left off (on any device), create a queue, and receive recommendations based on your viewing habits.
You can’t get something for nothing in this world; if you want to watch a show for free, you’re going to need to put up with an ad or two, both before and during the show — you know, just like in the olden days. The ads aren’t as intrusive as you might think. You’ll typically watch a 20-second ad before your show starts and then sit through a 40-second commercial about halfway through.
And partly because it’s owned by Fox, Tubi has a surprisingly deep well of content. Some of it might even be more recent than you’d expect. And that makes sense, because more recent (and popular) content draws in more views, and that means more eyeballs on advertising, and more money in everyone’s pocket.
Let’s not look this gift horse in the mouth, though: Tubi is free, and for that reason alone, it’s worth sifting through the catalog in the hopes of striking gold — which is happening more frequently lately. After all, if you find at least one thing you like, it was time well spent.
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In summary, we don’t think makes sense to have Tubi as your only streaming service. But it is a no-risk platform with some really interesting and quality niche content for fans. And with the growth of AVOD and FAST services such as Tubi, Pluto, Plex, The Roku Channel, Amazon FreeVee and more, customers are thinking more about dumping their subscription services like Hulu, Netflix, and Disney+, and putting up with ads, which may not be as intrusive as you might think. Either way, adding a free-streaming service like Tubi to your roster is risk-free, so why wouldn’t you?
Apple finally introduced the new iPhone 16 series earlier this month. The Cupertino tech giant has now begun shipping the new iPhones to the early buyers. As soon as the iPhone 16 started shipping, the first teardown video of the iPhone 16 Pro surfaced online. YouTube channel REWA Technology has posted a teardown video of the iPhone 16 Pro, which gives us a sneak peek at all the internals of the new iPhone.
The teardown shows that Apple has made a lot of design changes under the hood of the new iPhones. Notably, another YouTube channel Disassembling Parts has posted a teardown of the iPhone 16 Pro Max variant.
iPhone 16 Pro teardown reveals a compact and more densely packed motherboard
As you can see in the teardown video below, the iPhone 16 Pro features a considerably smaller motherboard. Compared to the iPhone 15 Pro, the motherboard on the 16 Pro is smaller and is more densely packed. Furthermore, the overall layout of the components is quite different. The new iPhone 16 Pro model also features better heat dissipation too. However, the tighter space could make repairs harder.
A metal-encased battery, larger camera assembly, and non-removable Camera Control button
Furthermore, the iPhone 16 Pro video reveals that Apple has packed the phone with a metal-encased battery. This is expected to aid with heat dissipation. Also, the 3,582mAh battery is 9.4 percent larger than the 3,274mAh power-cell of its predecessor.
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The teardown shows that the camera assembly on the iPhone 16 is larger than the one on its predecessor. This is due to the inclusion of the 12MP periscope telephoto lens. However, the selfie camera module is slightly smaller this time around.
The video also reveals that the new Camera Control button is non-removable as it is laser welded. Also, the company has separated the microphone from the charging port. The inner shell of the new iPhone is made from aluminum and graphite.
iPhone 16 Pro Max teardown reveals its battery is still encased in black foil
The iPhone 16 Pro Max’s teardown video shows that the bigger phone’s battery is still encased in black foil. You may be wondering why this one’s battery isn’t encased in steel. Well, this is due to the large size of the iPhone 16 Pro Max, which automatically provides better heat dissipation. Since there’s a lot more internal room, the company could get by without putting the phone’s battery in a steel case.
Generative AI is the single dominant trend in data management and analytics. Nothing else is even close.
It’s been that way since OpenAI launched ChatGPT in November 2022. The technology marked a significant improvement in the capabilities of large language models (LLMs) and showed the transformative potential of GenAI in the enterprise.
One key possibility is to be assistive in nature, with GenAI-powered natural language processing enabling virtually any employee — not just data scientists and other analysts — to use business intelligence tools to inform decisions. Due to the complex nature of most data management and analytics platforms, computer science skills, statistical expertise and data literacy training were all prerequisites before generative AI reduced those obstacles.
Another key possibility that has made generative AI such a singular data and analytics trend is exponentially improved efficiency. Generative AI applications can be trained to be agents unto themselves that take on time-consuming, repetitive tasks that data engineers and other experts previously needed to do manually.
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But while GenAI first became a major trend because of its potential, it is evolving.
ChatGPT’s launch was closely followed by the development and release of a spate of competing LLMs. Initially, the technology’s transformative capabilities were theoretical. Now, they are becoming a reality, according to Yasmeen Ahmad, Google’s managing director of strategy and outbound product management for data, analytics and AI.
Now, vendors including Google are developing generative AI tools to better enable customers to use their platforms to build GenAI models and applications. Enterprises, meanwhile, are taking advantage and creating pilot models while going through the proof-of-concept phase.
Generative AI, however, doesn’t exist in a vacuum. As a result, enterprises are emphasizing complementary capabilities such as data quality and data governance, which aim to ensure that the information feeding and training GenAI can be trusted. In addition, real-time data and automation are key to making sure that generative AI isn’t a reactive technology.
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Yasmeen Ahmad
Ahmad recently took time to discuss why generative AI has been such a pervasive trend in data management and analytics, including its assistive and agentive nature as well as its potential for unlocking unstructured data that has long been difficult to operationalize.
In addition, she spoke about other data management and analytics trends and how they are complementing generative AI to advance what enterprises can do with data.
Editor’s note:This Q&A has been lightly edited for clarity and conciseness.
Generative AI has obviously been a major trend over the past couple of years. Is it accurate to say it’s been the top trend in data management and analytics?
Yasmeen Ahmad: One hundred percent. Generative AI has been a massive trend across multiple dimensions. Generative AI is a fundamental technology that is truly transforming the way data platforms are being built, the way data platforms are being used — a lot of enterprise data has been dark — and then generative AI is changing the way that humans are working. It’s transforming their experience. It’s a big trend because it’s so multifaceted and multilayered in the impact it’s having across all these different dimensions.
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Generative AI is a fundamental technology that is truly transforming the way data platforms are being built, the way data platforms are being used … and then generative AI is changing the way that humans are working. Yasmeen AhmadManaging director of strategy and outbound product management for data, analytics and AI, Google
You addressed this in part in your last answer, but to delve a little deeper, what does generative AI enable that makes it such a dominant trend in data and analytics?
Ahmad: Generative AI is a fundamental technology transforming the landscape of data management and analytics in two very important dimensions. First, what we see from organizations is that 80% to 90% of enterprise data today is unstructured. It’s PDFs, documents, images, videos. That is data that has not traditionally been analyzed. We didn’t have the tool set. Generative AI is the tool set to unlock multimodal data that previously was inaccessible. That, in itself, opens up new insights, new use cases that weren’t possible before.
In addition, combining multimodal data with traditional structured data adds to and enhances traditional analytics. Gartner reported that 66% of enterprise data is dark data. Generative AI is eliminating that dark data.
What are some of the use cases you alluded to that weren’t previously possible?
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Ahmad: We have a customer, Symphony Communications, that is using generative AI with call center transcript data. It’s audio data that previously might have been tagged manually to capture some data to do sentiment analysis. Now, with audio transcripts, they can get deep, rich, meaningful insights by analyzing the words. They can generate responses that a call center agent can read to a customer live, in real time. Beyond that, they can get much more nuanced to understand what customers are talking about, what the sentiment is. They have the ability to do translation on the fly. They have all of this rich analysis that wasn’t previously possible. That’s one example.
Another is HCA Healthcare. They’re using Google’s BigQuery and BigLake multimodal data foundation to bring together traditional structured patient data with documents and notes from clinicians and physicians and with image data from X-rays and MRIs. Traditionally, they analyzed the structured data to look for trends in their patient population. What they were not able to do was bring together that rich data you get with physician notes and with images to really do analysis around diagnoses and look at patient healthcare. They’re using generative AI with traditional models to improve healthcare in a way they just weren’t able to before.
Where are enterprises in their generative AI development cycle — are they still in the idea stage or have they moved to the development and production stages?
Ahmad: We are seeing very fast innovation in the generative AI space with customers accelerating through the exploratory phase of pilot testing and proof-of-concepts to getting into pilot production. With many generative AI use cases, we still see a human in the loop — they’re not fully automating the generative AI technology. But they are putting it into the hands of their businesspeople, business users, to drive outcomes. I’ve never before seen this pace of innovation with a new technology.
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What makes that pace of innovation possible?
Ahmad: The key is that generative AI isn’t a new technology where you have to start an entirely new data platform or ecosystem. The way it’s being built is that generative AI models are being integrated into existing data platforms, the ability to run a large language model over existing data. There’s an ability to tap very quickly into low-hanging fruit. Then, as customers are maturing, we’re seeing 600% year-over-year growth in using multimodal data.
There’s a gravitational pull toward bringing more multimodal data sets to expand the use cases they were doing initially. There’s a lot of exploration happening to understand its potential. We’re seeing massive exploration as customers understand how this technology fits into their landscape, how it’s going to transform their business. And today, there’s lots of human-driven generative AI, but we’re already seeing that in the future it’s going to be generative AI assisted by humans.
There’s been a huge amount of buzz around generative AI that’s made it such a big trend in data management and analytics — is it living up to the hype?
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Ahmad: Technologies are typically overestimated in the near term and underestimated in the long term. That analogy absolutely applies to generative AI. There’s massive amounts of hype and energy around what it can do that’s now being broken down to figure out how to get to business results. But the long-term implications of this technology are transformational. I lean into the idea that it is as big as the internet or mobile phones in terms of the transformational impact it can have on so many parts of everyday life for us as humans and consumers and patients, and also for businesses in the way that they operate and meet the needs of those humans, consumers and patients.
As generative AI moves beyond hype and more enterprises develop pilot models, what are they discovering about the reality of generative AI development?
Ahmad: For enterprises, doing initial use cases and getting to insights in pilots has been great. But generative AI is shining a light on the data platform. The challenge is no longer on having an AI technology — generative AI has made that easy. The challenge is how to make sure there’s a trusted AI-ready data foundation. With generative AI, the efficacy of models is linked to data, the quality of high-volume data needed for training, for tuning, for RAG [retrieval-augmented generation].
The No. 1 conversation we’re now having with customers is about making sure their enterprise data is ready, it’s trusted, it’s governed, especially as they bring together multimodal data foundations. They want to govern all that data the same way they governed traditional structured data, so they need a single access control and governance pane across diverse types of data, and they need to easily use that data for LLM training, tuning, RAG and prompting.
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We’ve spoken extensively about generative AI, so what are some other major trends in data management and analytics?
Ahmad: Still related to generative AI are the ideas of assistive and agentic experiences. Data governance and data quality are top concerns. Often, the No. 1 thing C-suite executives talk to me about is data governance and how to trust their data. What we’re seeing is that generative AI can support with that. It can be an assistive technology to understand data drift, finding data anomalies and even building and generating metadata and semantics. And we know semantics are important when training generative AI models because semantics give models context about a business, the language of a business, and help generative AI give more accurate and precise answers.
Traditionally, a human had to build all those semantics and curate all that data and manage the quality. We’re actually applying generative AI to manage that problem because it has the ability to generate semantics by looking at the data, looking at relationships. We see generative AI as a massive accelerator for data engineering teams that had a lot of human toil.
If that’s the assistive nature of generative AI, what is the agentic?
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Ahmad: It’s the notion of data agents that operate on the data analytics lifecycle and transform the experience. Rather than a human coming to data and asking for an insight or for data quality to be improved, a data agent is monitoring data, looking for anomalies, surfacing insights, suggesting semantic modeling metrics to monitor. We’re moving from a reactive world to one where generative AI is proactive in supporting the data analytics lifecycle. The agentic world is supported by the evolution we’re seeing with LLMs.
As we evolve LLMs, it’s not just about the size of the model increasing, the parameter size increasing. Of course that’s improving quality, but at the LLM scale, we’re starting to see emergent capabilities where they’re able to reason much better, understand causality. That leads to LLMs being able to reason and understand if the answers it’s giving are 100% accurate and whether there are nuances to the answers. They’re getting better at evaluating their own answers. That’s what will power a more agentic future where an organization will have data agents that essentially power the enterprise.
What about other data management and analytics trends — what else are you seeing enterprises emphasize?
Ahmad: Two others we’re seeing are real time and automation. When you bring generative AI together with real time and automation, now you can truly deliver the transformation businesses are looking for. With digitalization, businesses were able to get much more data about themselves. Now that we’re in a world where more data is being captured, the next evolution is to use generative AI for intelligence with real time to be able to generate outputs and action them in real time. So, we’re seeing an uptick in streaming. Historically, we were feeding real-time pipelines with aged insights. Now, [enterprises] can run machine learning and LLMs over real-time streams of data and pipeline out real-time actions. There’s a flywheel of getting real-time data in, running generative AI and automating it all. It’s that true transformation that businesses have been waiting for.
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Great innovation comes from bringing together diverse pieces of technology that together create more innovation, and this feels like a moment when pieces of technology are coming together that can drive transformation.
What’s the timeline for converging those technologies to transform business?
Ahmad: We have the entire stack from the foundational technology layer to the LLMs to the data platforms with real-time streaming data. The integrated stack exists today. Over the last two years, we’ve placed a heavy emphasis on unification and simplification because to power this transformation, you need unified platforms and simplified, integrated technology. Google has an open ecosystem, so there are integrations between Google technologies plus integrations with partners. Integration and unification is a key pillar. That foundation is needed to build a transformative world.
Eric Avidon is a senior news writer for TechTarget Editorial and a journalist with more than 25 years of experience. He covers analytics and data management.
Yasmeen Ahmad
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