generative – 第 2 页 – Tech Magazine xi39 news

CIOs' concerns over generative AI echo those of the early days of cloud computing

2024-07-28

Image Credits: gremlin / Getty Images

When I attended the MIT Sloan CIO Symposium in May, it struck me that as I listened to CIOs talking about the latest technology — in this case generative AI — I was reminded of another time at the same symposium in around 2010 when the talk was all about the cloud.

It was notable how similar the concerns over AI were to the ones that I heard about the fledgling cloud all those years ago: Companies were concerned about governance (check), security (check) and responsible use of a new technology (check).

But 2010 was just at the edge of the consumerization of IT where workers were looking for the same type of experience they had at home at work. Soon, they would resort to “shadow IT” to find those solutions on their own when IT said no, and no was the default in those days. It was easy enough for employees to go off on their own unless things went into total lockdown.

Today, CIOs recognize if they just say no to generative AI, employees are probably going to find a way to use these tools anyway. There are plenty of legitimate concerns when it comes to this technology — like hallucinations or who owns the IP — but there are also concerns about security, compliance and controls, especially around data, that large organizations demand and require.

But CIOs speaking at the conference were much more realistic than they had been 15 years ago, even if they had similar concerns.

“You know, everything’s out there and democratized,” said Mathematica CIO Akira Bell, speaking on a panel called “Sustaining Competitive Advantage in the Age of AI.”

“I think somebody else this morning already said, ‘You know, we can’t control this moment.’ We cannot and don’t want to be ‘the agents of no,’ to tell everybody what they can and cannot do, but what we can do is make sure people understand the responsibility they have as actors and users of these tools.”

Bell said that today, instead of saying no, she’s pushing responsible use of the technology and looking for ways to enhance their customers’ experience with AI. “So one is about governing, making sure our data is ready to be used, making sure our employees understand what best practices exist as they go on and use them.”

She said that the second piece is really thinking about how they use generative AI to enhance their core capabilities, and how they might use it on behalf of clients to create or amplify or change existing service offerings to their customers.

Bell said you must also look at the security component, so all of these things matter. Her organization can offer guidance on how to use these tools in a way that is consistent with the values of the company without shutting down access.

Angelica Tritzo, CIO at GE Vernova, a new spinout from GE focused on alternative energy, is taking a deliberate approach to implementing generative AI. “We have a number of pilots in different maturity stages. We probably, like many others, do not fully understand the full potential, so the cost and the benefit is not always fully aligned,” Tritzo told TechCrunch. “We are finding our way with all the pieces of technology, how much to partner with others versus what we need to do ourselves.” But the process is helping her learn what works and what doesn’t and how to proceed while helping employees get familiar with it.

Chris Bedi, who was CDIO (chief digital information officer) at ServiceNow, said that things will change in the coming years as employees start demanding access to AI tools. “From a talent standpoint, as organizations look to retain talent, which is a hot topic, it doesn’t matter what job function, people want their job talent to stay. I think it’ll be unthinkable to ask your company employees to do their jobs without GenAI,” Bedi told TechCrunch. What’s more, he believes the talent will start demanding it and question why you would want them to do work manually. (Bedi’s title recently changed to chief customer officer.)

To that end, Bedi says his company is committed to teaching its employees about AI and how to create an AI-literate workforce because people won’t necessarily understand without guidance how to make best use of this technology.

“We created some learning pathways, so everybody in the company had to take their AI 101,” he said. “We created that and selectively [levels] 201 and 301 because we know the future is AI, and so we have to get our whole workforce comfortable with it,” he said.

All of this suggests that while the concerns may be the same as they were in the last wave of technological change, IT executives have perhaps learned some lessons along the way. They understand now that you can’t just lock it down. Instead they have to find ways to help employees use generative AI tools safely and effectively because if they don’t, employees will probably start using them anyway.

CIOs' concerns over generative AI echo those of the early days of cloud computing

2024-07-08

by admin with No Comment Tech

Image Credits: gremlin / Getty Images

But CIOs speaking at the conference were much more realistic than they had been 15 years ago, even if they had similar concerns.

“You know, everything’s out there and democratized,” said Mathematica CIO Akira Bell, speaking on a panel called “Sustaining Competitive Advantage in the Age of AI.”

Chris Bedi, CDIO (chief digital information officer) at ServiceNow, said that things will change in the coming years as employees start demanding access to AI tools. “From a talent standpoint, as organizations look to retain talent, which is a hot topic, it doesn’t matter what job function, people want their job talent to stay. I think it’ll be unthinkable to ask your company employees to do their jobs without GenAI,” Bedi told TechCrunch. What’s more, he believes the talent will start demanding it and question why you would want them to do work manually.

Music video-sharing app Popster uses generative AI and lets artists remix videos

2024-07-04

by admin with No Comment Tech

Image Credits: Popster

As more music streaming apps and creation tools emerge to compete for users’ attention, social music-sharing app Popster is getting two new features to grow its user base: an AI image generator for cover art and a collaboration capability where artists can remix another user’s song.

Initially launched last year as a song-creation tool and music video platform, Popster allows artists to engage with other musicians, create original songs and music videos, and share them on social media. Users can record video and voice directly in the app and add stickers and color backgrounds. The app also offers a selection of vocal effects (created in-house) and a community section for artists to interact with each other.

The app has, naturally, jumped on the generative AI bandwagon as well. For instance, it provides ways for artists to generate ideas for lyrics as well as create new beats to record vocals on top. (Popster also uses AI tech to enhance the audio if there’s background noise.)

One notable AI-powered tool is the “Add a beat” feature. Users can select a genre (Lofi Hip Hop, R&B, Indie Pop, Slow Ballad and so on) and a vibe like “Smooth” or “Normal” to compose a backtrack for singers to add their voice recordings on top.

Popster uses Mubert’s library of royalty-free pre-made tracks, distinguishing itself from AI music apps Udio and Suno, both of which recently faced lawsuits for allegedly using copyrighted music without authorization.

“The issue with AI right now is that many people create songs that are trained from original songs, so you don’t know who is the original creator, and there’s not this concept of creativity,” co-founder and CEO Themis Drakonakis told TechCrunch. “We believe that if you put AI next to the artist as a creative partner, you can experiment with [different sounds], unlock different ideas, and get your creativity to another level.”

Popster’s new artwork generator, “Albums,” is the newest addition to its generative AI tools (which are all powered by OpenAI). In addition to being able to record and upload videos, Popster now allows artists to enter a prompt to generate an image that can be displayed like a sticker overlay on top of an artist’s short-form video. This adds an extra layer of sophistication for new and up-and-coming artists trying to introduce their new songs into the world.

Another one of Popster’s new features appears to be its take on TikTok’s “Stitch” and “Duet” tools, which artists frequently use to combine their videos with other creators to add vocals, harmonize or play instruments. Popster’s new “Mashup” feature lets artists create remixes and collaborate with other artists. Users can now click the “Mashup” button under another person’s video and record their own video, which will appear side-by-side.

Popster co-founders Themis Drakonakis (left) and Sotiris Kaniras (right)

Popster is still in its early days, with only a few thousand users. However, Popster’s latest features may be what it needs to attract more people. So far, nearly 10,000 original songs have been created on the app. Drakonakis told us that users spend an average of 1.5 hours on the app daily.

The startup was co-founded by Drakonakis and Sotiris Kaniras (CTO). They previously created three other apps: Nup, an anonymous chat app; Self’it, a location-based photo-sharing app; and UniPad, a collaboration app for college students.

Popster raised $280,000 from the Realize Tech Fund and is in the midst of raising a pre-seed funding round, which will help it grow its team and enhance its video server. Other future plans include launching paid features and teaming up with music labels.

The app is available for download on the App Store.

Updated 7/3/24 at 3:30 pm ET with the correction that the beat generator is not powered by OpenAI. Popster also doesn’t have an app for Android devices.

Amazon extends generative AI-powered product listings to Europe

2024-06-20

by admin with No Comment Tech

Image Credits: Worayuth Kamonsuwan via Getty

Amazon is bringing its generative AI listing smarts to more sellers, revealing today that those in France, Germany, Italy, Spain, and the U.K. can now access tools designed to improve product listings by generating product descriptions, titles, and associated details.

Additionally, sellers can also “enrich” existing product listings by automatically adding missing information.

The announcement comes nine months after Amazon first revealed plans to bring generative AI technology to sellers. The company hasn’t been overly forthcoming with its availability on a market-by-market basis, but presumably it has largely been limited to the U.S. so far, though the company did quietly launch the tools in the U.K. earlier this month, according to an Amazon forum post. And in its blog post today, the company said that it rolled out this feature in the U.K. and some EU markets “a few weeks ago,” with more than 30,000 of its sellers apparently using at least of these AI-enabled listing tools in the intervening timeframe.

Amazon pitches these new tools as a way to enable sellers to list goods more quickly. The seller heads to their List Your Products page as usual, where they can begin by entering some relevant keywords that describe their product and simply hit the Create button to formulate the basis of a new listing. The seller can also generate a listing by uploading a photo via the Product image tab.

Amazon marketing image for generative AI-powered listings

Amazon will then magic up a product title, bullet point, and description which can be left as is, or edited by the seller. However, given the propensity for large language models (LLMs) to hallucinate, it wouldn’t be prudent to post a listing unchecked — a point that Amazon acknowledges by recommending that the seller reviews the copy “thoroughly” to ensure everything is correct.

“Our generative AI tools are constantly learning and evolving,” the company announced in its U.K. forum two weeks back. “We’re actively developing powerful new capabilities to make generated listings more effective, and make it even easier for you to list products.”

Earlier this year, Amazon also launched a new tool that allows sellers to generate product listings by posting a URL to their existing website. It’s not clear when, or if, Amazon will be extending this functionality to Europe or other markets outside the U.S.

The data question

While Amazon is no stranger to AI and machine learning across its vast e-commerce empire, bringing any form of AI to European markets raises some potential issues around regulation. There’s GDPR on the data privacy side for starters, not to mention the Digital Services Act (DSA) on the algorithmic risk side, with Amazon’s online store designated as a Very Large Online Platform (VLOP) for the purposes of ensuring transparency in the application of AI.

For context, Meta last week was forced to pause plans to train its AI on European users’ public posts following regulatory pressure. And Amazon itself has faced the wrath of EU regulators in the past over its mis-use of merchant data, when it was alleged that Amazon tapped non-public data from third-party sellers to benefit its own competing business as a retailer. And just this month, U.K. retailers hit Amazon with £1.1 billion lawsuit over similar accusations.

While Amazon’s latest foray into generative AI is a different proposition, it will have had to have trained its LLMs on some sort of data — what data this is, precisely, isn’t clear. In its initial announcement last September, Amazon shared a quote from its VP of Selection and Catalog Systems, Robert Tekiela, which referred to “diverse sources of information.”

With our new generative AI models, we can infer, improve, and enrich product knowledge at an unprecedented scale and with dramatic improvement in quality, performance, and efficiency. Our models learn to infer product information through the diverse sources of information, latent knowledge, and logical reasoning that they learn. For example, they can infer a table is round if specifications list a diameter or infer the collar style of a shirt from its image.
Robert Tekiela, VP of Amazon Selection and Catalog Systems

TechCrunch has reached out to Amazon for comment on these various issues, and will update when — or if — we hear back.

Robot holds a green check mark and red x on a purple background.

Building a viable pricing model for generative AI features could be challenging

2024-06-15

by admin with No Comment Tech

Image Credits: tommy / Getty Images

In October, Box unveiled a new pricing approach for the company’s generative AI features. Instead of a flat rate, the company designed a unique consumption-based model.

Each user gets 20 credits per month, good for any number of AI tasks that add up to 20 events, with each task charged a single credit. After that, people can dip into a company pool of 2,000 additional credits. If the customer surpasses that, it would be time to have a conversation with a salesperson about buying additional credits.

Box CEO Aaron Levie explained that this approach provides a way to charge based on usage with the understanding that some users would take advantage of the AI features more than others, while also accounting for the cost of using the OpenAI API, which the company is using for its underlying large language model.

Meanwhile, Microsoft has chosen a more traditional pricing model, announcing in November that it would charge $30 per user per month to use its Copilot features, over and above the cost of a normal monthly Office 365 subscription, which varies by customer.

While it became clear throughout last year that enterprise software companies would be building generative AI features, at a panel on generative AI’s impact on SaaS companies at Web Summit in November, Christine Spang, co-founder and CTO at Nylas, a communications API startup, and Manny Medina, CEO at sales enablement platform Outreach, spoke about the challenges that SaaS companies face as they implement these features.

Spang says, for starters, that in spite of the hype, generative AI is clearly a big leap forward, and software companies need to look for ways to incorporate it into their products. “I’m not going to say it’s like 10 out of 10 where the hype meets the [current] reality, but I do think there is real value there and what’s really going to make the difference is how people take the technology and connect it to other systems, other apps and sort of drive real value in different use cases with it,” she said.

It’s also about finding a balance between providing the kind of features that customers are suddenly demanding, and figuring out a way to price it in a way that provides real customer value, yet allows the company to make money. “In reality, those of us who are bundling [generative AI features] need to repeatedly check back with our [large language model] provider, and that’s going to get expensive quickly. So until we create experiences that are 10x differentiated, and for which somebody wants to pay for it, it’s going to be challenging,” Medina said.

It’s worth noting that model makers like OpenAI are already announcing price cuts as they find ways to run models more efficiently, or cut prices on older products as new ones are announced. For example, in June, the company announced some new features that increase processing power, which provide more bang for the buck, while also lowering the cost of prior versions for developers who don’t require all the latest bells and whistles.

Spang says her company is already using a consumption model based on the number of connected email or calendar applications, and she expects to follow a similar approach as they add generative AI features.

“We already have the case where some people send a lot more messages, or they receive a lot more messages and I think it’s important to map [to a similar pricing model] that people understand, and then hopefully we can find a price point that kind of works through the median,” she said.

But Medina says for an application, it’s more difficult to use a consumption model than an API provider like Nylas. “I just don’t know that that’s an acceptable model in applications. When you’re a provider of Legos [like Nylas], it’s a different story, but for application providers, [it’s more difficult],” he said.

But it’s also not clear that companies will be willing to pay a flat rate like Microsoft’s $30 a month per user for Office 365, unless they can see real value from that additional cost. “The jury’s still out until somebody either lowers the cost and it makes it very accessible for the rest of us, or we figure out a way to monetize it,” Medina said.

One big unknown also is the compliance costs that could be related to using this technology, which remains a big open question for companies and their customers. “So if you start embedding some of these applications and the U.S. [or other government] passes a law where you have to disclose the list of ingredients of your AI, you’re not getting that from OpenAI, so that’s going to be difficult,” he said.

CIOs who control the company technology budget are taking a close look at this technology, but they are still trying to figure out if the extra cost being passed on to them will pay for itself in terms of higher employee productivity.

Sharon Mandell, CIO at Juniper Networks, says she is looking closely at the ROI on these features. “In 2024, we’re going to be testing the GenAI hype, because if those tools can produce the types of benefits that they say, then the ROI on those is high and may help us eliminate other things,” she said. So she and other CIOs are running pilots, moving cautiously and trying to find ways to measure whether there is truly a productivity increase to justify the increased cost.

Regardless, companies will continue to experiment with pricing models, while their customers are conducting pilots and proofs of concept. It seems like they both have something to gain here, but until we start to see more of these tools in production, it’s hard to know the real benefits to everyone involved.

When it comes to generative AI in the enterprise, CIOs are taking it slow

Walmart debuts generative AI search and AI replenishment features at CES

2024-06-15

by admin with No Comment Tech

Image Credits: SAUL LOEB/AFP / Getty Images

In a keynote address at the Consumer Electronics Show in Las Vegas, Walmart president and CEO Doug McMillon and other Walmart execs offered a glimpse as to how the retail giant was putting new technologies, including augmented reality (AR), drones, generative AI and other artificial intelligence tech to work in order improve the shopping experience for customers.

At the trade show, the company revealed a handful of new products, including two AI-powered tools for managing product search and replenishment, as well as a new beta AR social commerce platform called “Shop with Friends.” It also highlighted how it was using AI in other areas of its business, including within Sam’s Club and in apps used by store associates.

Most notably, Walmart is launching a new generative AI search feature on iOS that will allow customers to search for products by use cases, instead of by product or brand names. For example, you could ask Walmart to return search results for things needed for a “football watch party,” instead of specifically typing in searches for chips, wings, drinks or a 90-inch TV. These enhanced search results will span categories, rivaling Google’s SGE (Search Generative Experience), which can recommend products and show various factors to consider, along with reviews, prices, images and more.

Ahead of CES, the company had demonstrated an AI shopping assistant that would let customers interact with a chatbot as they shopped, to ask questions and receive personalized product suggestions, as well. At the time, Walmart teased that a generative AI-powered search feature was also in the works. It suggested customers could ask for things like a “unicorn-themed birthday party” and get results like unicorn-themed napkins, balloons, streamers and more. Now the feature is rolling out on mobile devices, iOS first.

Another potentially promising use of AI involves the replenishment of frequently ordered items.

Walmart will initially test this use case with Walmart InHome Replenishment, which will use AI and its existing replenishment expertise combined to create automated online shopping carts for customers with items they regularly order. Because it’s only available through the InHome program, these items are then delivered to a customer’s fridge in their kitchen or garage using the smart lock-powered InHome delivery service, but it will not be a subscription service.

The company also noted that customers will be able to remove items from their basket, as needed, and the service will adjust to customer’s changing needs over time.

However, if the feature works well, it’s not hard to imagine how it could be put to use to offer replenishment of other household items as well, similar to Amazon’s Subscribe-and-Save.

Surprisingly, Amazon has not yet leveraged AI to do the same (i.e. to augment or replace Dash Replenishment). However, the online retailer has been putting AI to work in other ways, including by helping connect customers with the right product by summarizing product reviews, highlighting key attributes or helping them find clothes that fit.

Another new Walmart product making a debut at CES is “Shop with Friends,” an AR shopping tool that lets customers share virtual outfits they create with their friends and then get feedback on their finds. The tool combines Walmart’s AI-powered virtual try-on tech, launched last year, with social features.

CEO Doug McMillon referred to the suite of new products as something he called “adaptive retail” — that is, retail experiences that are personalized and flexible.

“While omnichannel retail has been around for decades, this new type of retail — adaptive retail — takes it a step further, said Suresh Kumar, global chief technology officer, and chief development officer, Walmart Inc., in a statement shared ahead of the CES keynote. “It’s retail that is not only e-commerce or in-store, but a single, unified retail experience that seamlessly blends the best aspects of all channels. And for Walmart, adaptive retail is rooted in a clear focus on people,” he said.

The company touched on other ways it’s employing AI, as well.

Walmart’s Sam’s Club will introduce an AI and computer vision-powered technology that helps solve the problem of waiting in line for receipt verification when exiting the store. The pilot, currently running in 10 locations, will confirm members have paid for their items without requiring a store associate to check their charts. Instead, computer vision tech will capture images of customers’ carts and AI will speed the process of matching cart items to sales. Walmart expects to bring the tech to its nearly 600 clubs by year-end.

In another area, Walmart’s generative AI tool for store associates, My Assistant, will be expanded to 11 countries outside the U.S. in 2024, where it will work in employees’ native languages. Already, the tool has become available in Canada, Mexico, Chile, Costa Rica, El Salvador, Honduras, Guatemala and Nicaragua and is on track for launches in India and South Africa. My Assistant helps employees with writing, summarizing large documents and offering “thought starters” to spark creativity, Walmart says.

On the matter of AI, McMillon stressed that the company wouldn’t prioritize the technology without considering the potential implications. Instead, Walmart’s “underlying principle is that we should use technology to serve people and not the other way around,” he said.

Still, McMillon admitted that AI will mean some jobs will be eliminated.

“No doubt some tasks will go away and some roles will change. And some of them should, like the ones that involve lifting heavy weights or doing repetitive tasks,” the exec explained. “As that’s happening, we’re designing new roles that our associates tell us are more enjoyable and satisfying, and also often result in higher pay. So we’re investing to help our associates transition to this shared future,” McMillon added.

During the keynote, McMillon also brought Microsoft CEO Satya Nadella onstage, after announcing that Walmart used large language models from Azure OpenAI alongside its own retail-specific models.

Nadella spoke broadly about the breakthroughs made possible with generative AI, including in areas like coding, productivity apps, like Microsoft’s own, healthcare, education and more, adding that with new technology, “one has to be mindful that you want to be able to amplify the opportunity with it…and then also be very mindful of the unintended consequences of this technology.”

Outside of AI, Walmart is looking to other new technology for faster deliveries.

The company announced it’s expanding its drone delivery service in the Dallas-Ft. Worth metro to 1.8 million households, or 75% of the metroplex area. The deliveries, which take place in 30 minutes or less, are powered by Wing and Zipline. Walmart also notes that 75% of the 120,000 items in a Walmart Supercenter meet the size and weight requirements for drone delivery. To date, Walmart has done over 20,000 drone deliveries in its two-year trial.

Walmart experiments with generative AI tools that can help you plan a party or decorate

Building a viable pricing model for generative AI features could be challenging

2024-05-26