The Alibaba Damo Academy is a unique hybrid research and development (R&D) facility. An academically-oriented independent science organization established in 2017 in Hangzhou, China, it is also an arms-length research affiliate of its founder, Chinese internet technology giant Alibaba. Damo’s project development pipelines are positioned around developing data-enabled technologies for fundamental business and social challenges, such as alleviating traffic congestion in mega-cities and workforce productivity in logistics. But the approach to solving these foundational problems is purposefully focused on commercialization-centric principles and development, which Damo’s leaders believe help shorten their development cycle and improve the efficiency of their scientific research.
Damo’s approach to R&D is a founding principal linked to an even deeper strategic objective: that the academy must “outlast Alibaba,” to become an enduring, sustainable, and independent developer of all of the group’s technology innovation. Yet, while Damo grows “out from under the shade of Alibaba’s tree,” (to paraphrase one of company founder Jack Ma’s favorite metaphors), the parent is still vital to its success: the technological and operational challenges of Alibaba’s business ecosystem serve as a source of inspiration for Damo.
Damo categorizes its technology projects into “emergent” (cutting-edge technology), “mature discussion” (market-ready technology), and “commercialized” (ready to be a product). “Commercialized” projects and some “mature discussion” projects are tightly connected to Alibaba’s technology development processes through a virtuous R&D circuit, which aims to quickly bring concepts to market through a frugal innovation process that uses lightweight, scalable, and sharable development resources: more than 80% of the projects run by Damo’s Voice Recognition Lab, for instance, host their applications on the cloud.
Such applications include AI-enabled medical image analysis technology, which Damo says can conduct coronary pneumonia clinical tests in under two seconds and deliver a full diagnosis with 99% accuracy in 20 seconds, which helps hospitals greatly accelerate their diagnosis process. A robotics division at Damo is trialling an autonomous last-mile logistics robot, inspired by the strain China’s fast-growing e-commerce demand is placing on door-to-door delivery services. The robot can potentially make 500 deliveries over 100 kilometers a day on four kilowatt-hours of electricity, navigating complex road and urban conditions and distinguishing between the action of pedestrians and vehicles.
Big brains for big city problems
Still other Damo projects attempt to address a number of organizational and social challenges through cross-functional, multi-application programs. A primary example of this are Damo’s projects using natural language processing in AI-enabled digital assistants to increase operational efficiency in businesses. Seeking to lift the capabilities of office-based smart speakers beyond the fairly rudimentary interactions that consumers have with their devices (largely simple verbal commands to conduct internet searches or navigate e-commerce sites), Damo has developed a prototype natural conversation analysis tool called ting wu (Chinese for listen and understand). It is designed to listen to meetings with multiple participants and will parse discussion patterns to produce informative synopses and assign post-meeting action items.
Damo’s speech model has also been used to develop a simultaneous translation service for AliExpress (Alibaba’s global retail marketplace), which is embedded in its customer engagement platform and allows participating merchant suppliers to translate from Chinese to English, Russian, Spanish, and French. The service was launched during last year’s Alibaba global shopping festival (also known as Singles’ Day) on November 11, and Damo reports that 70% of its merchant clients used the service. The technology was also used for the company’s customer service chatbot Alime, which served over 50 million active users on the company’s e-commerce sites Taobao and Tmall during Singles’ Day.
Grounded, but reaching for the clouds
Rather than being guided by formal key performance indicators, R&D direction is defined by five key terms, according to Xu Yinghui, Alibaba Group vice president and head of Damo’s Vision Lab, all of which underpin the academy’s focus on practical innovation. “The first is scalable: we want all our applications to have a big impact, and keeping things at the demo state is meaningless. The second is interpretable: we have to turn the black boxes of algorithms and other new tools into white boxes. The third is speed, then affordability, and then public benefit—so that as many as possible can enjoy the technology,” says Xu.
Jin Rong, an Alibaba Group vice president and the director of Damo’s Machine Intelligence Lab, believes that the academy’s “demand-oriented” R&D approach distinguishes it from other research institutes. “Good technologies should have application prospects and should effectively solve practical problems—not just technological, but organizational, or operational. Projects are established for specific market needs, and research and development results are quickly implemented in business and application scenarios,” says Jin. This culminates in a productization process “where the technology is deposited on our cloud platform as soon as possible,” ensuring both wider scalability and accessibility, as well as ongoing cost efficiency—the “engineering of controllable costs,” in Alibaba parlance. “It is an early-or-late issue, but not a yes-or-no issue,” says Jin.
In this sense, Damo’s cost and time constraints promote innovation: in order to make projects business viable, cost efficiency needs to be baked into the thesis. While Damo’s AI research is deep and significant, freewheeling experimentation untethered by practical application is frowned upon. “First, an idea must survive on its own in the real world rather than in one’s mind,” says Hua Xiansheng, head of City Brain Lab at the academy. Damo’s leaders believe it is this ethos that has driven the academy to swiftly claim numerous breakthrough projects in such wide-ranging foundational sectors like new computing architecture and autonomous driving, and in industrial applications across sectors including health care, logistics, transport and education sectors. Driven to solve deep, pernicious and socially significant problems, but with an embedded pragmatism, Damo is keen to keep growing far out from its parent’s shade.
This content was produced by Alibaba Damo Academy. It was not written by MIT Technology Review’s editorial staff.
The Download: COP28 controversy and the future of families
The United Arab Emirates is one of the world’s largest oil producers. It’s also the site of this year’s UN COP28 climate summit, which kicks off later this week in Dubai.
It’s a controversial host, but the truth is that there’s massive potential for oil and gas companies to help address climate change, both by cleaning up their operations and by investing their considerable wealth and expertise into new technologies.
The problem is that these companies also have a vested interest in preserving the status quo. If they want to be part of a net-zero future, something will need to change—and soon. Read the full story.
How reproductive technology can reverse population decline
Birth rates have been plummeting in wealthy countries, well below the “replacement” rate. Even in China, a dramatic downturn in the number of babies has officials scrambling, as its population growth turns negative.
So, what’s behind the baby bust and can new reproductive technology reverse the trend? MIT Technology Review is hosting a subscriber-only Roundtables discussion on how innovations from the lab could affect the future of families at 11am ET this morning, featuring Antonio Regalado, our biotechnology editor, and entrepreneur Martín Varsavsky, founder of fertility clinic Prelude Fertility. Don’t miss out—make sure you register now.
Unpacking the hype around OpenAI’s rumored new Q* model
While we still don’t know all the details, there have been reports that researchers at OpenAI had made a “breakthrough” in AI that had alarmed staff members. Reuters and The Information both report that researchers had come up with a new way to make powerful AI systems and had created a new model, called Q* (pronounced Q star), that was able to perform grade-school-level math. According to the people who spoke to Reuters, some at OpenAI believe this could be a milestone in the company’s quest to build artificial general intelligence, a much-hyped concept referring to an AI system that is smarter than humans. The company declined to comment on Q*.
Social media is full of speculation and excessive hype, so I called some experts to find out how big a deal any breakthrough in math and AI would really be.
Researchers have for years tried to get AI models to solve math problems. Language models like ChatGPT and GPT-4 can do some math, but not very well or reliably. We currently don’t have the algorithms or even the right architectures to be able to solve math problems reliably using AI, says Wenda Li, an AI lecturer at the University of Edinburgh. Deep learning and transformers (a kind of neural network), which is what language models use, are excellent at recognizing patterns, but that alone is likely not enough, Li adds.
Math is a benchmark for reasoning, Li says. A machine that is able to reason about mathematics, could, in theory, be able to learn to do other tasks that build on existing information, such as writing computer code or drawing conclusions from a news article. Math is a particularly hard challenge because it requires AI models to have the capacity to reason and to really understand what they are dealing with.
A generative AI system that could reliably do math would need to have a really firm grasp on concrete definitions of particular concepts that can get very abstract. A lot of math problems also require some level of planning over multiple steps, says Katie Collins, a PhD researcher at the University of Cambridge, who specializes in math and AI. Indeed, Yann LeCun, chief AI scientist at Meta, posted on X and LinkedIn over the weekend that he thinks Q* is likely to be “OpenAI attempts at planning.”
People who worry about whether AI poses an existential risk to humans, one of OpenAI’s founding concerns, fear that such capabilities might lead to rogue AI. Safety concerns might arise if such AI systems are allowed to set their own goals and start to interface with a real physical or digital world in some ways, says Collins.
But while math capability might take us a step closer to more powerful AI systems, solving these sorts of math problems doesn’t signal the birth of a superintelligence.
“I don’t think it immediately gets us to AGI or scary situations,” says Collins. It’s also very important to underline what kind of math problems AI is solving, she adds.
The Download: unpacking OpenAI Q* hype, and X’s financial woes
This is today’s edition of The Download, our weekday newsletter that provides a daily dose of what’s going on in the world of technology.
Unpacking the hype around OpenAI’s rumored new Q* model
Ever since last week’s dramatic events at OpenAI, the rumor mill has been in overdrive about why the company’s board tried to oust CEO Sam Altman.
While we still don’t know all the details, there have been reports that researchers at OpenAI had made a “breakthrough” in AI that alarmed staff members. The claim is that they came up with a new way to make powerful AI systems and had created a new model, called Q* (pronounced Q star), that was able to perform grade-school level math.
Some at OpenAI reportedly believe this could be a breakthrough in the company’s quest to build artificial general intelligence, a much-hyped concept of an AI system that is smarter than humans.
So what’s actually going on? And why is grade-school math such a big deal? Our senior AI reporter Melissa Heikkilä called some experts to find out how big of a deal any such breakthrough would really be. Here’s what they had to say.
This story is from The Algorithm, our weekly newsletter giving you the inside track on all things AI. Sign up to receive it in your inbox every Monday.
I’ve combed the internet to find you today’s most fun/important/scary/fascinating stories about technology.
1 X is hemorrhaging millions in advertising revenue
Internal documents show the company is in an even worse position than previously thought. (NYT $)
+ Misinformation ‘super-spreaders’ on X are reportedly eligible for payouts from its ad revenue sharing program. (The Verge)
+ It’s not just you: tech billionaires really are becoming more unbearable. (The Guardian)
2 The brakes seem to now be off on AI development
With Sam Altman’s return to OpenAI, the ‘accelerationists’ have come out on top. (WSJ $)
+ Inside the mind of OpenAI’s chief scientist, Ilya Sutskever. (MIT Technology Review)
3 How Norway got heat pumps into two-thirds of its households
Mostly by making it the cheaper choice for people. (The Guardian)
+ Everything you need to know about the wild world of heat pumps. (MIT Technology Review)
4 How your social media feeds shape how you see the Israel-Gaza war
Masses of content are being pumped out, rarely with any nuance or historical understanding. (BBC)
+ China tried to keep kids off social media. Now the elderly are hooked. (Wired $)
5 US regulators have surprisingly little scope to enforce Amazon’s safety rules
As demonstrated by the measly $7,000 fine issued by Indiana after a worker was killed by warehouse machinery. (WP $)
6 How Ukraine is using advanced technologies on the battlefield
The Pentagon is using the conflict as a testbed for some of the 800-odd AI-based projects it has in progress. (AP $)
+ Why business is booming for military AI startups. (MIT Technology Review)
7 Shein is trying to overhaul its image, with limited success
Its products seem too cheap to be ethically sourced—and it doesn’t take kindly to people pointing that out. (The Verge)
+ Why my bittersweet relationship with Shein had to end. (MIT Technology Review)
8 Every app can be a dating app now
As people turn their backs on the traditional apps, they’re finding love in places like Yelp, Duolingo and Strava. (WSJ $)
+ Job sharing apps are also becoming more popular. (BBC)
9 People can’t get enough of work livestreams on TikTok
It’s mostly about the weirdly hypnotic quality of watching people doing tasks like manicures or frying eggs. (The Atlantic $)
10 A handy guide to time travel in the movies
Whether you prioritize scientific accuracy or entertainment value, this chart has got you covered. (Ars Technica)
Quote of the day
“It’s in the AI industry’s interest to make people think that only the big players can do this—but it’s not true.”
—Ed Newton-Rex, who just resigned as VP of audio at Stability.AI, says the idea that generative AI models can only be built by scraping artists’ work is a myth in an interview with The Next Web.
The big story
The YouTube baker fighting back against deadly “craft hacks”
Ann Reardon is probably the last person you’d expect to be banned from YouTube. A former Australian youth worker and a mother of three, she’s been teaching millions of subscribers how to bake since 2011.
However, more recently, Reardon has been using her platform to warn people about dangerous new “craft hacks” that are sweeping YouTube, such as poaching eggs in a microwave, bleaching strawberries, and using a Coke can and a flame to pop popcorn.
Reardon was banned because she got caught up in YouTube’s messy moderation policies. In doing so, she exposed a failing in the system: How can a warning about harmful hacks be deemed dangerous when the hack videos themselves are not? Read the full story.
We can still have nice things
+ London’s future skyline is looking increasingly like New York’s.
+ Whovians will never agree on who has the honor of being the best Doctor.
+ How to get into mixing music like a pro.
+ This Japanese sea worm has a neat trick up its sleeve—splitting itself in two in the quest for love.
+ Did you know there’s a mysterious tunnel under Seoul?