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.
We’ve rebooted regular ticket prices for TechCrunch Disrupt 2024, giving you one last chance to save big before the event. Enjoy up to $600 off individual tickets until September 27.
Disrupt 2024 is the ultimate startup hub, taking place at Moscone West in San Francisco from October 28-30. Join 10,000 startup, tech, and VC leaders; engage with top minds in over 200 sessions of meaningful discussions; gain valuable insights from industry giants; and so much more.
Listen to leading industry voices as they dive into the startup and tech ecosystem across six industry-specific stages — AI, SaaS, Fintech, Builders, Space, and the Main Disrupt Stage.
A highlight of every Disrupt has always been Startup Battlefield 200, where a few chosen startups will pitch to a panel of top VC leaders. The winner will earn a $100,000 equity-free prize and the coveted Disrupt Cup.
The judging panel includes industry heavyweights like Christine Esserman, partner at Accel; Sangeen Zeb, general partner at Google Ventures; Alice Brooks, partner at Khosla Ventures; Victor Lazarte, general partner at Benchmark; and many more.
Their feedback offers valuable insight into what makes a startup successful. Get a front-row seat to this expert evaluation and discover the qualities that drive success, only at Disrupt 2024.
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Unparalleled networking
Make the right connections at every phase of your career or startup journey. Whether you’re a first-time founder, a seasoned entrepreneur, a recent graduate looking for your first tech job, or someone transitioning after a layoff, Disrupt offers networking opportunities for everyone.
Connect with fellow attendees in the bustling Expo Hall, the central hub for all 10,000 Disrupt participants. Discover groundbreaking innovations from pre-seed startups and industry leaders in this dynamic space.
Dive into detailed discussions through 1:1 or small-group Braindates. Use the Braindate app to post or look for your topics of interest, and then connect face-to-face in the Braindate Lounge at the event to delve deeper into these ideas. It’s a great way to have impactful conversations with like-minded professionals.
Continue the excitement of the main event during “Disrupt Week,” running from October 26 to November 1. With more than 50 Side Events, including happy hours, comedy nights, workshops, and meetups, you’ll find countless opportunities to connect and engage after hours.
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Explore more than 200 sessions designed to build connections and delve into key issues with industry experts, focusing on the pressing challenges encountered by today’s entrepreneurs.
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The Plucky Squire is a game that leaps off the page — literally. It takes place in a storybook world rendered in an adorable two dimensions thanks to codirector and former Pokémon artist James Turner. But at certain points, the heroic lead character can venture into the real world and solve puzzles that mix 2D and 3D in inventive ways. Sometimes, you’re moving objects between dimensions; other times, you’re rearranging the words in a book to create new outcomes. It’s as cute as it is creative, and it follows Sony’s Astro Bot in what is turning out to be a very good year for family-friendly games.
The game puts you in the role of Jot, the titular plucky squire, who has the unusual ability to exist outside of the book he stars in. The two worlds are drastically different: inside the storybook is bright, colorful, and simple, while the real world is appropriately dark and realistic. They’re distinct, but through Jot, the worlds intersect as he sets about saving the book from an evil wizard. Solving puzzles involves flipping through pages to pull items from the past, using language to bypass barriers, and occasionally boxing a bear. It’s silly and heartfelt and, at times, calls to mind the 2D segments in Nintendo classics Super Mario Odyssey and The Legend of Zelda: A Link Between Worlds.
“The idea of contrast was really important to the game.”
For Turner, the initial idea for the game came during a lull, when he had just left Pokémon developer Game Freak but hadn’t yet started work at All Possible Futures, the studio he cofounded with Jonathan Biddle. “I left Game Freak, and then I had nothing to do,” he tells The Verge. “To fill that void, I started drawing a webcomic.” That comic, called Cosmic, included a number of characters and ideas that would eventually make their way into The Plucky Squire as its storybook narrative took shape.
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For Turner — who frequently posts hilarious mashup illustrations and who designed notable pokémon like Polteageist — one of the goals of the game was to create a unique clash of styles. Not only should the dimensions in The Plucky Squire play different, but they should look different as well. It’s an idea that came about early in development; initially, when Jot jumped into the real world, he was cel-shaded to keep his cartoony style. Eventually, though, it became clear that a more realistic, almost toy-like version of the character worked better.
Image: All Possible Futures
“It reduced the realism of the outside world quite significantly in a strange way,” Turner says of the cel shading. “Even though the outside world was very real, if the object that you’re looking at 90 percent of the time [isn’t], it starts to affect how you see the rest of the world.” He adds that “the idea of contrast was really important to the game.”
A good example is early on in The Plucky Squire when Jot is in search of a bow-and-arrow to complete a quest. This involves jumping through a portal into the real world, navigating a very messy desk filled with obstacles, and then jumping into a card ripped out of Magic: The Gathering to battle an elf. When Jot finally reaches his destination, there are three distinct art styles onscreen: storybook 2D, realistic 3D, and detailed fantasy art. “I thought that clash of styles would be the most jaw-dropping,” Turner explains.
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“There’s a big gap outside of Nintendo.”
Outside of its visuals, The Plucky Squire is also notable for being an experience that works really well for all ages. The action and puzzles have just enough depth to them to be satisfying while not being intimidating for younger or less experienced players. It’s like a streamlined Zelda adventure, with some nice quality-of-life features, like an optional hint system that doesn’t give too much away. It’s a style of game that can be hard to find outside of something from Nintendo (which includes the upcoming Echoes of Wisdom). But titles like Astro Bot and The Plucky Squire are showing it’s possible for other developers, as well.
“There are lots of people that want to play those games, and they haven’t been catered to as much as they possibly should have been,” says Turner. “It does feel like there’s a big gap outside of Nintendo where it would be nice if we had those games more regularly. There’s a need for them.”
The Plucky Squire is out now on the Nintendo Switch, PlayStation, Xbox, and PC.
Quordle was one of the original Wordle alternatives and is still going strong now nearly 1,000 games later. It offers a genuine challenge, though, so read on if you need some Quordle hints today – or scroll down further for the answers.
What letters do today’s Quordle answers start with?
• Z
• M
• A
• D
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Right, the answers are below, so DO NOT SCROLL ANY FURTHER IF YOU DON’T WANT TO SEE THEM.
Quordle today (game #972) – the answers
(Image credit: Merriam-Webster)
The answers to today’s Quordle, game #972, are…
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It’s been a while since we’ve had an uncommon letter in Quordle – you’d have to go back to SEIZE on September 10. And as with that game, it was a Z that appeared today to make things more complicated. I needed all nine guesses to complete today’s puzzle, partly due to that letter tripping me up for ZESTY, but it wasn’t the only word I struggled with. DRAWN also caused me problems (and W is another fairly uncommon letter), and this wasn’t a game I sailed through with ease.
In a basement beneath City St George’s, University of London, senior leaders from NATO watch as four research teams from the UK, US, Netherlands and Austria, showcase their AI-controlled, autonomous drones. The groups are competing against each other as part of the NATO-funded SAPIENCE programme, designed to accelerate progress with this emerging technology, particularly in a world where drones on the battlefield are changing warfare, as demonstrated in Ukraine.
“We are still trying to understand what are the impacts of drones,” says Claudio Palestini, head of NATO’s Science for Peace and Security programme. “We have regular contact with Ukraine where we understand what they are doing with technology,” he says. “NATO is adapting to this new way of fighting, we are developing some concepts in the drone warfare sphere.”
While there are applications on the battlefield, Palestini is keen to stress that there is a dual nature to NATO’s work. “What we do [at NATO’s Science for Peace and Security programme], it’s not purely military,” he says. “We want to have technology development that can be used in the commercial sector, but also in the defence sector. And this is where cooperation with Ukraine helps.” Such work has echoes of the US Defense Advanced Research Projects Agency (DARPA).
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In London, the first of four events gets under way, simulating an indoor search and rescue scenario in an environment where GPS won’t work that is akin to the aftermath of a natural disaster. The team from City St George’s deploys two autonomous drones working cooperatively in a swarm configuration, with deep-learning algorithms driving navigation.
“We’re the only ones that used a neural network,” says Thomas Hickling, a PhD student and member of the team, highlighting how the group thinks this form of AI is better for mapping damaged infrastructure. Speed and reliability are also considerations, especially in life-saving scenarios. “We decided to use two drones as it’s much quicker and increases reliability,” says Hickling. “If one drone fails, you’ve got another one automatically. You can take over the jobs of the other drone.”
Future SAPIENCE events will test the teams’ technology in outdoor and mixed environments, performing a range of simulated tasks. While presented as a competition, Palestini sees this as a driving force behind acceleration and cooperation in the field. “We don’t expect to have a single winner,” he says. “We will have some sort of ranking, but all the ideas are good.”
Believe it or not, there’s only been one live-action Marvel series on Disney+ in 2024 prior to September. The nine-month drought is over thanks to the arrival of Agatha All Along, giving fans of WandaVision a semi-sequel series. But we might have to wait until March 2025 for the next Marvel show if there’s really nothing between Agatha All Along and Daredevil: Born Again.
In the meantime, younger Star Wars fans also have something to enjoy this month called LEGO Star Wars: Rebuild the Galaxy. It’s a pretty wild take on the Star Wars universe, as only LEGO could provide. But if you want more mature fare, Disney’s going to make you shell out more for Hulu just so you can watch Shogun, The Bear, Only Murders in the Building, and other shows on the Disney+ app that you already have. If that makes you unhappy, just remember that Disney+ is raising its prices again in October. Surely that will bring a smile to your face as you look over the best shows on Disney+ right now.
If you’re not already subscribed, the Disney Bundle is worth considering. With it, you get Disney+, ESPN, and the ad-supported Hulu plan, making it an impressive value for the price. You’ll enjoy new Disney content, live sports coverage, and Hulu’s various originals.
OxygenOS, the heart of the OnePlus smartphones, is currently on its version 14. The company is now working on the OxygenOS 15 update. The brand will unveil the latest iteration of its custom Android skin in late September or early October, suggest the reports. While the brand hasn’t teased much about the upcoming version, folks over at SmartPrix have revealed quite a few details. It looks like the OxygenOS 15 takes inspiration from iOS and will borrow a lot of features from Apple’s OS.
Many core UI elements of OxygenOS 15 take heavy inspiration from iOS
People over at the tech publication SmartPrix were able to get an opportunity to beta-test OxygenOS 15. The source suggests that OxygenOS 15 takes heavy inspiration from iOS and brings an iOS-like volume panel, Dynamic Island-like notifications, and more. The OxygenOS 15 update will bring a brand new Control Center design. The source says the new Control Center looks like “If HyperOS and iOS had a baby”.
OnePlus took inspiration from iOS while designing the volume panel in OxygenOS 15. The new volume slider will “start out as a larger slider but shrinks to a narrow width” when you tap on it again, just like in iOS. The source highlights that swiping down from the top right of the display will trigger the Quick Settings panel.
If you swipe down from the left, you will get the notification shade. Also, the OnePlus users will be able to customize the Quick Settings panel as per their liking by rearranging tiles.
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A Dynamic Island-inspired notification system is coming with the OxygenOS 15 update
Furthermore, the report suggests that A Dynamic Island-inspired notification system is coming to OnePlus devices with the upcoming OxygenOS update. Much like the Dynamic Island on iOS, it will now sit on top of the center punch hole. In addition, the camera app on a phone running OxygenOS 15 allows you to shoot live photos. Once again, this is very much like iOS, which calls it Live Photos.
Notably, the source suggests that the OnePlus users will not have to wait too long to test out the aforementioned features. The first beta version of OxygenOS 15 is expected to be released by the end of this month. If that doesn’t happen then early October is the best bet.
Yasmeen Ahmad
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