Meta lets businesses create ad-embedded chatbots

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The apps Instagram, Facebook and WhatsApp can be seen on the display of a smartphone in front of the logo of the Meta internet company.

Image Credits: Jens Büttner/picture alliance / Getty Images

At the Meta Connect 2024 developer conference in Menlo Park on Wednesday, Meta announced that it’s expanding its AI-powered business chatbots to brands on WhatsApp and Messenger using click-to-message ads.

Now businesses can set up ad-embedded chatbots that talk to customers, offer support, and facilitate orders, Meta says. “From answering common customer questions to discussing products and finalizing a purchase, these business AIs can help businesses engage with more customers and increase sales,” the company wrote in a blog post provided to TechCrunch.

Meta business chatbots
Image Credits: Meta

Meta continues to inject more of its ad products and tools with AI. In May, the company began letting advertisers create full new ad images with AI and insert AI-generated alternate versions of ad headlines. And in June, Meta began testing AI-powered customer support for businesses using WhatsApp, which automatically answers customer queries related to frequently asked questions.

Meta claims that more than a million advertisers are using its AI ad tools and that 15 million ads were created with the tools last month.

AI ads boost click-through rates, Meta says. But there’s evidence to suggest customers may not like ads with chatbots. One survey commissioned earlier this year by customer experience platform Callvu found that the majority of people would rather wait at least a minute to speak with a live customer agent than chat instantly with an AI.

Data platform Airbyte can now create API connectors by reading the docs

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Robot sitting on a bunch of books

Image Credits: Kirillm / Getty Images

If your startup is only remotely related to working with data pipelines, you’re probably trying to figure out how to capitalize on the current moment: Enterprises are trying to figure out how to best use data to power generative AI products, and to do that, they need robust data services. Airbyte, which launched in 2020, started with a focus on building a low-code/no-code open source data integration platform. Since then, Airbyte raised a total of $181.2 million, including a massive $150 million Series B round during the somewhat anomalous days of late 2021.

After four years, the company is now launching Airbyte 1.0 — and the focus, of course, is on AI, both as an addition to Airbyte’s own tools and to help its users build their own AI-based services.

Indeed, the company is now leveraging AI in a clever way to expand on its overall low-code/no-code philosophy: Its model will be able to look at the documentation for an API and automatically create a connector based on that. You simply point it at the documentation, and it’ll handle the rest (at least in theory; time will tell how well that works in practice, of course.)

As Airbyte co-founder and CEO Michel Tricot told me, he believes that one area where large language models are transforming how enterprise use their data is by making unstructured data far more useful — and usable.

“Structured data is just the tip of the iceberg when it comes to leveraging data’s full potential,” he said. “With the rise of LLMs, we can now efficiently tap into previously untouched unstructured data. … We’ve seen massive demand for handling multi-modal data. Our latest developments have been geared toward supporting intelligent, context-aware pipelines, optimizing frameworks like RAG, and automating pipeline creation based on customer data workflows. These innovations are crucial to unlocking advanced use cases and enhancing LLM performance.”

Because Airbyte is now so much better at managing unstructured data, its users can now leverage their existing pipelines to do that, without having to rely on additional tools.

In non-AI news, Airbyte’s connector now also supports GraphQL, which should help users access many additional datasets without even having to build custom pipelines.

With this release, Airbyte is also making its self-managed enterprise service generally available. Like with so many open source companies, the enterprise version, which is available on the AWS and GCP marketplaces, will offer features like single sign-on (SSO) and role-based access control (RBAC), as well as Airbyte-specific features like sensitive data masking and advanced observability.

Airbyte says it has 7,000 enterprise customers and has seen over 170,000 deployments by now. Its customers range from Calendly and Coupa to Perplexity AI and Siemens.

“Every company is a data company — to drive decision-making and as the foundation for AI initiatives,” Tricot said. “Only Airbyte, with our open source strategy enabling hundreds of connectors, can give enterprises the ability to leverage any data they choose. As AI continues to drive transformation, we’re delivering the technology and ecosystem required for organizations to build the data infrastructure needed for AI-driven innovation.”

CuspAI raises $30M to create a GenAI-driven search engine for new materials

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CuspAI cofounders Prof Max Welling and Dr Chad Edwards

Image Credits: CuspAI co-founders Prof. Max Welling and Dr. Chad Edwards / CuspAI

The modern method of coming up with new materials is to make something and then use a computer to work out whether the material came out correctly. But what if you flipped that around, using generative-AI-driven software to design the material in the first place? That’s the premise behind Cambridge, U.K.-based CuspAI, which has now secured $30 million in a seed round led by Hoxton Ventures, with significant participation from Basis Set Ventures and Lightspeed Venture Partners.

As co-founder and CEO Chad Edwards put it, “We’re flipping the old process on its head and saying, ‘Well, if you can put materials or molecules in and get properties out, then why can’t you put properties in and get materials and molecules?’”

The market is dominated by players such as Schrodinger (listed on NASDAQ) and Dassault Systemes, both of which provide software tools to perform computational chemistry and material simulations.

Newer on the block is Orbital Materials, which includes part of the team behind Google’s DeepMind and has an AI-powered platform that can be used to discover materials ranging from batteries to carbon dioxide-capturing cells. It recently raised $16 million in a Series A.

“In the same way that search engines enabled the internet, we believe we’re on the cusp of a world in which you can search the very, very large space of new materials and molecules to discover new materials that have exactly the desired properties. We think we’re entering the ‘materials-on-demand’ era,” he said.

Indeed, the company says its platform functions like a search engine for materials, enabling the fast evaluation of a “vast number of novel structures.”

“Civilization has always defined itself by the materials of that time so, bronze age, stone age, etc. We think we’re going into the materials-on-demand age,” he added.

CuspAI launched only this year and seems to have its work cut out for it. However, Edwards is not exactly starting from scratch. 

His co-founder is Max Welling, a professor and renowned pioneer in AI. He was also formerly the Distinguished Scientist and VP at Microsoft Research and Qualcomm, and was a professor at the University of Amsterdam. “Our AI can generate and evaluate new materials on demand. For example, you can request a material that selectively binds carbon dioxide under specified conditions — the AI then generates, evaluates and optimises the potential molecular structures that meet those exact criteria,” he said in a statement.

Edwards is a chemist who has been involved in deep tech commercialization at Google and BASF and most recently at quantum computing leader, Quantinuum.

Geoffrey Hinton, known as the “Godfather of AI,” will also serve as a board adviser. 

In a statement, Hinton said: “Humanity will face many challenges in the coming decade. Some will be caused by AI while others can be solved by AI. I’ve been very impressed by CuspAI and its mission to accelerate the design process of new materials using AI to curb one of humanity’s most urgent challenges: climate change.”

An area where CuspAI thinks AI-designed materials could have a significant near-term impact is carbon capture and storage.

“We’re looking at the the design of molecular sponges that selectively absorb carbon dioxide from the air,” Edwards said. “When you heat them up, they release carbon dioxide, which you can pipe it off and make use of, or bury it underground, whatever you want to do.”

CuspAI has also partnered with Meta on its open science project to discover new materials to address climate change. 

“The Fundamental AI Research (FAIR) team is looking forward to collaborating with CuspAI in their use of AI, including our OpenDAC work, to accelerate the discovery of novel DAC sorbent materials,” Yann LeCun, VP and Chief AI Scientist at Meta, said in a statement. “The world needs fast progress on affordable carbon capture, and we believe that CuspAI’s team is in an excellent position to apply AI-based materials discovery to this pressing problem.”

Other investors in the round include LocalGlobe, Northzone, Touring Capital, Giant Ventures, FJ Labs, Tiferes Ventures and Zero Prime Ventures. Angel investors, including Mehdi Ghissassi and Dorothy Chou from DeepMind, also participated.

CuspAI raises $30M to create a GenAI-driven search engine for new materials

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CuspAI cofounders Prof Max Welling and Dr Chad Edwards

Image Credits: CuspAI co-founders Prof. Max Welling and Dr. Chad Edwards / CuspAI

The modern method of coming up with new materials is to make something and then use a computer to work out whether the material came out correctly. But what if you flipped that around, using generative-AI-driven software to design the material in the first place? That’s the premise behind Cambridge, U.K.-based CuspAI, which has now secured $30 million in a seed round led by Hoxton Ventures, with significant participation from Basis Set Ventures and Lightspeed Venture Partners.

As co-founder and CEO Chad Edwards put it, “We’re flipping the old process on its head and saying, ‘Well, if you can put materials or molecules in and get properties out, then why can’t you put properties in and get materials and molecules?’”

The market is dominated by players such as Schrodinger (listed on NASDAQ) and Dassault Systemes, both of which provide software tools to perform computational chemistry and material simulations.

Newer on the block is Orbital Materials, which includes part of the team behind Google’s DeepMind and has an AI-powered platform that can be used to discover materials ranging from batteries to carbon dioxide-capturing cells. It recently raised $16 million in a Series A.

“In the same way that search engines enabled the internet, we believe we’re on the cusp of a world in which you can search the very, very large space of new materials and molecules to discover new materials that have exactly the desired properties. We think we’re entering the ‘materials-on-demand’ era,” he said.

Indeed, the company says its platform functions like a search engine for materials, enabling the fast evaluation of a “vast number of novel structures.”

“Civilization has always defined itself by the materials of that time so, bronze age, stone age, etc. We think we’re going into the materials-on-demand age,” he added.

CuspAI launched only this year and seems to have its work cut out for it. However, Edwards is not exactly starting from scratch. 

His co-founder is Max Welling, a professor and renowned pioneer in AI. He was also formerly the Distinguished Scientist and VP at Microsoft Research and Qualcomm, and was a professor at the University of Amsterdam. “Our AI can generate and evaluate new materials on demand. For example, you can request a material that selectively binds carbon dioxide under specified conditions — the AI then generates, evaluates and optimises the potential molecular structures that meet those exact criteria,” he said in a statement.

Edwards is a chemist who has been involved in deep tech commercialization at Google and BASF and most recently at quantum computing leader, Quantinuum.

Geoffrey Hinton, known as the “Godfather of AI,” will also serve as a board adviser. 

In a statement, Hinton said: “Humanity will face many challenges in the coming decade. Some will be caused by AI while others can be solved by AI. I’ve been very impressed by CuspAI and its mission to accelerate the design process of new materials using AI to curb one of humanity’s most urgent challenges: climate change.”

An area where CuspAI thinks AI-designed materials could have a significant near-term impact is carbon capture and storage.

“We’re looking at the the design of molecular sponges that selectively absorb carbon dioxide from the air,” Edwards said. “When you heat them up, they release carbon dioxide, which you can pipe it off and make use of, or bury it underground, whatever you want to do.”

CuspAI has also partnered with Meta on its open science project to discover new materials to address climate change. 

“The Fundamental AI Research (FAIR) team is looking forward to collaborating with CuspAI in their use of AI, including our OpenDAC work, to accelerate the discovery of novel DAC sorbent materials,” Yann LeCun, VP and Chief AI Scientist at Meta, said in a statement. “The world needs fast progress on affordable carbon capture, and we believe that CuspAI’s team is in an excellent position to apply AI-based materials discovery to this pressing problem.”

Other investors in the round include LocalGlobe, Northzone, Touring Capital, Giant Ventures, FJ Labs, Tiferes Ventures and Zero Prime Ventures. Angel investors, including Mehdi Ghissassi and Dorothy Chou from DeepMind, also participated.

CuspAI raises $30M to create a Gen-AI-driven search engine for new materials

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CuspAI cofounders Prof Max Welling and Dr Chad Edwards

Image Credits: CuspAI cofounders Prof Max Welling and Dr Chad Edwards

The modern method of coming up with new materials is to make something and then use a computer to work out whether the material came out correctly. But what if you flipped that around, using generative-AI-driven software to design the material in the first place? That’s the premise behind Cambridge, U.K.-based CuspAI, which has now secured $30 million in a seed round led by Hoxton Ventures, with significant participation from Basis Set Ventures and Lightspeed Venture Partners.

As co-founder and CEO Chad Edwards put it, “We’re flipping the old process on its head and saying, ‘Well, if you can put materials or molecules in and get properties out, then why can’t you put properties in and get materials and molecules?’”

The market is dominated by players such as Schrodinger (listed on NASDAQ) and Dassault Systemes, both of which provide software tools to perform computational chemistry and material simulations.

Newer on the block is Orbital Materialsm, from part of the team behind Google’s Deepmind, which has an AI-powered platform that can be used to discover materials ranging from batteries to carbon dioxide-capturing cells. It recently raised $16 million in a Series A.

“In the same way that search engines enabled the internet, we believe we’re on the cusp of a world in which you can search the very, very large space of new materials and molecules to discover new materials that have exactly the desired properties.We think we’re entering the ‘materials-on-demand’ era,” he said.

Indeed, the company says its platform functions like a search engine for materials, enabling the fast evaluation of a “vast number of novel structures.”

“Civilization has always defined itself by the materials of that time so, bronze age, stone age, etc. We think we’re going into the materials on demand age,” he added.

The company only launched this year, and CuspAI seemingly has its work cut out for it. However, Edwards is not exactly starting from scratch. 

His co-founder is Max Welling, a professor and renowned pioneer in AI. He was also formerly the Distinguished Scientist and VP at Microsoft Research and Qualcomm, and a professor at the University of Amsterdam. “Our AI can generate and evaluate new materials on demand. For example, you can request a material that selectively binds carbon dioxide under specified conditions — the AI then generates, evaluates and optimises the potential molecular structures that meet those exact criteria,” he said in a statement.

Edwards himslef is a chemist who has been involved in deep-tech commercialization at Google and BASF and most recently quantum computing leader, Quantinuum.

Geoffrey Hinton, known as the “Godfather of AI,” will also serve as a board adviser. 

In a statement, Hinton said: “Humanity will face many challenges in the coming decade. Some will be caused by AI while others can be solved by AI. I’ve been very impressed by CuspAI and its mission to accelerate the design process of new materials using AI to curb one of humanity’s most urgent challenges: climate change.”

An area where CuspAI thinks AI-designed materials could have a significant near-term impact is carbon capture and storage.

“We’re looking at the the design of molecular sponges that selectively absorb carbon dioxide from the air,” Edwards said. “When when you heat them up, they release carbon dioxide which you can pipe it off and make use of, or bury it underground, whatever you want to do.”

CuspAI has also partnered with Meta on its open science project to discover of new materials to address climate change. 

“The Fundamental AI Research (FAIR) team is looking forward to collaborating with CuspAI in their use of AI, including our OpenDAC work, to accelerate the discovery of novel DAC sorbent materials,” Yann Le Cun, VP and Chief AI Scientist at Meta, said in a statement. “The world needs fast progress on affordable carbon capture, and we believe that CuspAI’s team is in an excellent position to apply AI-based materials discovery to this pressing problem.”

Other investors in the round include LocalGlobe, Northzone, Touring Capital, Giant Ventures, FJ Labs, Tiferes Ventures and Zero Prime Ventures. Angel investors, including Mehdi Ghissassi and Dorothy Chou from Deepmind, also participated.

Robot humanoid use laptop and sit at table for global network connection

MLCommons wants to create AI benchmarks for laptops, desktops and workstations

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Robot humanoid use laptop and sit at table for global network connection

Image Credits: NanoStockk / Getty Images

As AI increasingly moves from the cloud to on-device, how, exactly, is one supposed to know whether such and such new laptop will run a generative-AI-powered app faster than rival off-the-shelf laptops — or desktops or all-in-ones, for that matter? Knowing could mean the difference between waiting a few seconds for an image to generate versus a few minutes — and as they say, time is money.

MLCommons, the industry group behind a number of AI-related hardware benchmarking standards, wants to make it easier to comparison shop with the launch of performance benchmarks targeted at “client systems” — that is, consumer PCs.

Today, MLCommons announced the formation of a new working group, MLPerf Client, whose goal is establishing AI benchmarks for desktops, laptops and workstations running Windows, Linux and other operating systems. MLCommons promises that the benchmarks will be “scenario-driven,” focusing on real end user use cases and “grounded in feedback from the community.”

To that end, MLPerf Client’s first benchmark will focus on text-generating models, specifically Meta’s Llama 2, which MLCommons executive director David Kanter notes has already been incorporated into MLCommons’ other benchmarking suites for datacenter hardware. Meta’s also done extensive work on Llama 2 with Qualcomm and Microsoft to optimize Llama 2 for Windows — much to the benefit of Windows-running devices.

“The time is ripe to bring MLPerf to client systems, as AI is becoming an expected part of computing everywhere,” Kanter said in a press release. “We look forward to teaming up with our members to bring the excellence of MLPerf into client systems and drive new capabilities for the broader community.”

Members of the MLPerf Client working group include AMD, Arm, Asus, Dell, Intel, Lenovo, Microsoft, Nvidia and Qualcomm — but notably not Apple.

Apple isn’t a member of the MLCommons, either, and a Microsoft engineering director (Yannis Minadakis) co-chairs the MLPerf Client group — which makes the company’s absence not entirely surprising. The disappointing outcome, however, is that whatever AI benchmarks MLPerf Client conjures up won’t be tested across Apple devices — at least not in the near-ish term.

Still, this writer’s curious to see what sort of benchmarks and tooling emerge from MLPerf Client, macOS-supporting or no. Assuming GenAI is here to stay — and there’s no indication that the bubble is about to burst anytime soon — I wouldn’t be surprised to see these types of metrics play an increasing role in device-buying decisions.

In my best-case scenario, the MLPerf Client benchmarks are akin to the many PC build comparison tools online, giving an indication as to what AI performance one can expect from a particular machine. Perhaps they’ll expand to cover phones and tablets in the future, even, given Qualcomm’s and Arm’s participation (both are heavily invested in the mobile device ecosystem). It’s clearly early days — but here’s hoping.

Topsort, advertising, e-commerce, retail media technology

Topsort helps e-commerce create ads without being ‘creepy’

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Topsort, advertising, e-commerce, retail media technology

Image Credits: Topsort

Regina Ye says she and Topsort co-founder Francisco Larrain have learned a lot in the two years since their auction-powered advertising startup launched.

The company raised $8 million in seed funding in 2022 to value the company at $110 million. Topsort develops retail media technology for small businesses to use auctions as a way to create effective advertising.

Fed up with how complex ad campaigns were to create on Meta, Amazon and Google, they created a simple API for users to install. When they start a campaign, customers can add items like sponsored listings, banner ads and video ads. They then control how the ads are shown, how to measure ad quality and relevance, and who can launch campaigns.

Topsort, an auction-based advertising startup, now valued at $110M after seed round

The founders also recognized that its plug-and-play product resonated with e-commerce marketplaces of different sizes. Today, Topsort is used by marketplaces in 35 countries by the likes of Poshmark and Youtravel.me.

“You don’t need to be a rocket scientist to be able to actually have really good advertising results,” Ye told TechCrunch. “We have tried many things since then and found what works, and last year was incredible growth for us. We grew almost 10 times in terms of revenue, and we have a similar scale of ambition for this year.”

Topsort also shifted its focus to be more enterprise-friendly, and it built more advanced features. It now counts P&G, General Mills and Danone, among others, as customers.

All that growth excited investors, who poured another $20 million of Series A capital into Topsort along with a valuation boost to $150 million post-money. Upload Ventures led the round with support from existing investors, including Quiet Capital and Pear Ventures. The company has now raised $28.6 million in total.

The company is focusing on what happens now that cookies are going away. Topsort wants to correct advertising’s reputation for being “slimy” around user privacy. It created a Cleanroom feature to combine user data without actually “being creepy,” Ye said.

“Everyone’s wondering what’s going to happen to advertising after cookies, and we think we have the answer to the clean advertising solution,” Ye said. “We’ve spent three years making a very solid offering, and today, we probably have the most comprehensive offering of that in the market.”

Where will our data go when cookies disappear?

Adobe is making it easier to create social content on mobile with AI

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photo illustration of an Adobe logo

Image Credits: Pavlo Gonchar/SOPA Images/LightRocket / Getty Images

Adobe is making it easier for users to create and publish social content on mobile, as the company announced today that it’s launching the latest version of the Adobe Express app in beta. With this update, Adobe is bringing its Firefly AI models directly into the app, allowing users to quickly create and edit social content using generative AI tools.

The latest version of the app will allow Adobe to better compete with Canva, which introduced a suite of AI tools last year.

Adobe Express users will get access to a new “Text to Image” generator that will allow them to quickly create a new look for a project by quickly generating images with Firefly generative AI. A new “Generative Fill” feature will let them use text prompts to easily insert, remove or replace people or objects. Plus, a new “Text Effects” feature will help users quickly makes messages pop by using different text stylings.

Adobe notes that small businesses can use these features to do things like remove unwanted objects and photos to enhance their promotional content, while creative professionals can use them to accelerate mobile content creation across their social marketing teams.

Image Credits: Adobe

Creative Cloud members can use the app to access and work on creative assets from Photoshop and Illustrator directly within Adobe Express. They can also add linked files that sync in Adobe Express as they edit in Creative Cloud apps.

The Adobe Express app lets you preview and publish content to social media platforms like TikTok and Instagram. It also lets you upload and share brand assets and use your specific brand’s colors and logos to speed up the design process. The app features access to thousands of video and multipage templates, along with Adobe Stock videos, music and images.

Android users can download the new Adobe Express app in beta from the Google Play store. Since Apple restricts the number of beta users in apps, iOS users need to sign up to get access to the beta app.

Today’s announcement comes a few weeks after Adobe and TikTok announced that TikTok’s AI-powered Creative Assistant is now available directly within Adobe Express. The two companies said the integration will help businesses and creators make and market content more effectively.

Adobe Firefly can now generate more realistic images

Amazon URL-based AI-powered listing tool

Amazon now lets sellers create listings through a URL by using AI

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Amazon URL-based AI-powered listing tool

Image Credits: Amazon

Amazon launched generative AI-powered features last year to help sellers quickly create listings by entering just a few words about the product. The company is now making it easier for sellers to create listings if an item is already listed on their website.

The e-commerce giant’s new tool uses AI to parse details from an item’s URL on another site and create an Amazon listing. The feature is rolling out in English to sellers in the U.S.

“In addition to using sparse amounts of text or an image to generate listings, we are now launching the ability for sellers to simply leverage their existing listings by just providing Amazon with a URL, which is automatically parsed by our generative AI-based features, to seamlessly create high-quality, engaging listings for Amazon’s store,” the company said on its blog.

Last October, Amazon rolled out a tool for advertisers to generate background through text prompts. At that time, the company said a contextual background to an item could generate a 40% more click-through rate as compared to a white background.

In the latest announcement, Amazon said more than 100,000 sellers have tried generative AI tools. The more interesting stat the company mentioned was that 80% of the time sellers accept suggestions from AI-powered tools.

Other companies have also dabbled into AI-powered tools related to products for advertisers and retailers. Last year, Google launched a tool related to product imagery and eBay introduced a feature that generated listings from product images. Earlier this year, Shopify rolled out its own AI-powered image editor for products.

Messenger now lets you create shared albums, send HD photos and share larger files

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Image Credits: Messenger

Meta announced on Tuesday it’s rolling out the ability for Messenger users to create shared albums in chats, send photos in high-definition, and share larger files up to 100MB in size. With these new features, Messenger is targeting people who tend to create shared albums or share HD images via services like Google Drive.

Up until now, users have only been able to see a list of photos shared in a specific Messenger chat and couldn’t group or organize them in any way. Now users can create albums of photos and videos in group chats, whether it’s to organize photos of a recent spring break or grandma’s 80th birthday celebration. To create an album in a group chat, you need to select multiple photos from your chat composer and then tap “create album.” You can also create an album by long-pressing a photo in a chat. If you want to add photos to an existing album, you can tap the “Add to album” option.

Everyone in a chat can view, add, delete, and download pictures and videos in an album. You can locate an album by tapping the “Media” button in a chat.

The launch of shared albums is likely to be a welcome addition for users, as the capability isn’t available on Meta’s other messaging services, WhatsApp and Instagram DMs.

Image Credits: Messenger

As for the new HD photo-sharing capability, users can now toggle an “HD” option after selecting an image from the chat composer. You can tap on additional photos to send multiple in HD. The launch of the new feature follows Meta’s rollout of support for HD photos on WhatsApp back in September 2023.

In addition, Messenger is offering an alternative to email for sending large files, as it’s now letting users send Word, PDF, Excel, and zip files directly in chats. Users can do so by tapping the + button in a chat and then selecting a file on their device.

Also new today is the launch of an option for users to connect with others by scanning a QR code, removing the need to type out someone’s name or number to start chatting with them on the app.

The new features are rolling out on mobile to all Messenger users.