Among the new AI features Apple announced at WWDC is hand washing detection for the Apple Watch. | Image: AppleAI has become an integral part of every tech company’s pitch to consumers. Fail to hype up machine learning or neural networks when unveiling a new product, and you might as well be hawking hand-cranked calculators. This can lead to overpromising. But judging by its recent WWDC performance, Apple has adopted a smarter and quieter approach.
Why blind them with science when you can charm them with convenience?Sprinkled throughout Apple’s announcements about iOS, iPadOS, and macOS were a number of features and updates that have machine learning at their heart. Some weren’t announced onstage, and some features that almost certainly use AI weren’t identified as such, but here’s a quick recap of the more prominent mentions that we spotted:
Facial recognition for HomeKit. HomeKit-enabled smart cameras will use photos you’ve tagged on your phone to identify who’s at your door and even announce them by name.Native sleep tracking for the Apple Watch. This uses machine learning to classify your movements and detect when you’re sleeping. The same mechanism also allows the Apple Watch to track new activities like dancing and…Handwashing. The Apple Watch not only detects the motion but also the sound of handwashing, starting a countdown timer to make sure you’re washing for as long as needed.App Library suggestions. A folder in the new App Library layout will use “on-device intelligence” to show apps you’re “likely to need next.” It’s small but potentially useful.Translate app. This works completely offline, thanks to on-device machine learning. It detects the languages being spoken and can even do live translations of conversations.Sound alerts in iOS 14. This accessibility feature wasn’t mentioned onstage, but it will let your iPhone listen for things like doorbells, sirens, dogs barking, or babies crying.Handwriting recognition for iPad. This wasn’t specifically identified as an AI-powered feature, but we’d bet dollars to donuts it is. AI is fantastic at image recognition tasks, and identifying both Chinese and English characters is a fitting challenge.There are absences in this list — most notably Siri, Apple’s perennially disappointing digital assistant. Although Siri is AI-heavy, it mostly got cosmetic updates this year (oh, and “20 times more facts,” whatever that means). A new interface is a welcome change for sure, but it’s small fry when you compare Siri’s overall performance with other AI assistants.
What these updates do show, though, is Apple’s interest in using machine learning to deliver small conveniences rather than some grand, unifying “AI” project, as some tech companies have promised with their own digital assistants, claiming to seamlessly improve your life by scheduling your calendar, preempting your commute, and so on.
This latter project was always going to be a failure as AI, for all its prowess, is basically just extremely good pattern-matching software. This has myriad uses — and some are incredibly unexpected — but it doesn’t mean computers can parse the very human complexities of something as ordinary as your calendar appointments, a task that relies on numerous unspoken rules about your priorities, routine, likes and dislikes, and more.
The best example of Apple’s approach is the new handwashing feature on the Apple Watch, which uses AI to identify when you’re scrubbing your mitts and starts a timer. It’s a small and silly feature, but one that asks little of the user while delivering a useful function.
This is a strong tactic for Apple that plays to the company’s long-held reputation — deserved or not — for delivering software that “just works.” It also avoids the sort of iterative, tech-for-tech’s-sake update that can fall flat with the average consumer, like Samsung’s Bixby.
By: James Vincent
Title: Apple’s AI plan: a thousand small conveniences
Sourced From: www.theverge.com/2020/6/25/21301511/apple-ai-machine-learning-features-wwdc-2020-convenience
Published Date: Thu, 25 Jun 2020 12:00:17 +0000
Did you miss our previous article…
Brothers in arms
William Warin Bainbridge Jr., Class of 1922, and Kenneth Tompkins Bainbridge, Class of 1926, grew up on Manhattan’s Riverside Drive, the eldest of three sons of an upwardly mobile stationer who dabbled in real estate. Both went to MIT. And both would play important roles in World War II—one on the front lines at Normandy and at the Battle of the Bulge, the other with J. Robert Oppenheimer in Los Alamos.
William Warin Bainbridge Jr., Class of 1922COURTESY OF DAVID BAINBRIDGE
Before making their way to MIT, the brothers attended the Horace Mann School, where they participated in athletics and Ken wrote for the newspaper and the humor magazine. But while Bill was playing hockey, Ken was busy exploring the new medium of radio. “I had a radio with an antenna on the roof [of the family townhouse],” he recalled in 1991. “The antenna and ground were connected across the vibrating contacts, which energized a commercial ultraviolet unit. I must have violated every bandwidth law.” Ken’s five-watt ham radio station had just three call letters: 2WN.
In 1918, Bill arrived at the Institute, where he majored in engineering administration. He belonged to a dizzying number of organizations, including two fraternities (Alpha Tau Omega and Theta Tau), the football team, the wrestling team (which he managed), and the finance and budget committees. Ken joined Bill at MIT in the fall of 1921 to study electrical engineering, ultimately earning both a bachelor’s and a master’s degree through a co-op program with General Electric that required him to spend time at GE’s offices in Lynn, Massachusetts, and summers at the GE campus in Schenectady, New York. Ken, too, pledged Alpha Tau Omega, and he served on the board of MIT’s Voo Doo humor magazine. Master’s in hand, Ken and an MIT friend were admitted in 1926 to the doctoral program in physics at Princeton, where the dean reportedly told them, “You’re nice boys, but it’s too bad you never went to college.”
Despite the dean’s skepticism, Ken rose quickly in the academic ranks—first at Princeton, where he became a pioneering mass spectroscopist; then at Cambridge University’s Cavendish Labs on a Guggenheim fellowship; and then at Harvard, where he built cyclotrons. Along the way, he published the results of an experiment confirming Einstein’s most famous equation, EMC2. He returned to MIT in 1940 to help found the Radiation Laboratory and played a key role in recruiting scientists and developing radar.
But on September 22, 1943, a letter to the local War Office from President Karl Taylor Compton noted that Bainbridge was unavailable for new local work because his “services were urgently requested by another scientific project of extreme urgency and secrecy.” Since MIT couldn’t refuse, Compton wrote that “Bainbridge was released from the Radiation Laboratory to participate in this new activity.”
The “activity” was “Project Y” at Los Alamos National Laboratory, where Ken and his cyclotron helped develop the first nuclear bomb.
Ken settled at Los Alamos with his wife, Margaret, formerly a member of the Swarthmore College faculty, and their three children. Under Oppenheimer’s direction, he took charge of the Initiator Committee and joined the “high-explosives” group. Then he was given the enormous responsibility of leading the effort to test the atomic bomb, which required working through countless technical and theoretical challenges. He was named head of Group E-9, “to study full-scale implosion assemblies and prepare for the Trinity test,” and Group E-2, which developed instrumentation for the test. In October 1944, Ken became a member of the detonator committee.
The other members of the Bainbridge family also threw themselves into the war effort. Mae, the matriarch, volunteered for the American Red Cross. Youngest brother Don, a Cornell grad, became a lieutenant in the Army Corps of Engineers. Bill, who’d been working in construction for US Gypsum, was commissioned at age 39 as a first lieutenant of the 342nd Engineers (he’d served previously as a second lieutenant early in his career). He headed to the UK in 1942 to become a regimental operations officer, using his building experience to supervise road stabilization and work that required the use of heavy earthmoving machines. By year’s end he’d been promoted to captain, and in 1943 he was transferred to the 254th Engineer Combat Battalion, V Corps.
By: Elisabeth C. Rosenberg
Title: Brothers in arms
Sourced From: www.technologyreview.com/2024/02/28/1087635/brothers-in-arms/
Published Date: Wed, 28 Feb 2024 12:00:00 +0000
Why shiny, high-tech solutions won’t solve one of Africa’s worst crises
Hainikoye hits Accept and a young woman greets him in Hausa, a gravelly language spoken across West Africa’s Sahel region. She has three new cows, and wants to know: Does he have advice on getting them through the lean season?
Hainikoye—a twentysomething agronomist who has “followed animals,” as Sahelians refer to herding, since he first learned to walk—opens an interface on his laptop and clicks on her village in southern Niger, where humped zebu roam the dipping hills and dried-up valleys that demarcate the northern desert from the southern savanna. He tells her where the nearest full wells are and suggests feeding the animals peanuts and cowpea leaves—cheap food sources with high nutritional value that, his screen confirms, are currently plentiful. They hang up after a few minutes, and Hainikoye waits for the phone to ring again.
Seven days a week at the Garbal call center, agents like Hainikoye offer what seems like a simple service, treating people to a bespoke selection of location-specific data: satellite-fed weather forecasts and reports of water levels and vegetation conditions along various herding routes, as well as practical updates on brushfires, overgrazed areas, nearby market prices, and veterinary facilities. But it’s also surprisingly innovative—and is providing critical support for Sahelian herders reeling from the effects of interrelated challenges ranging from war to climate change. Over the long term, the project’s supporters, as well as the herders connecting with it, hope it could even safeguard an ancient culture that functions as an economic lifeline for the entire region.
The glossy red cubicles of Garbal’s office in Niamey, Niger’s capital, are tucked away in the second-floor space the call center shares with the local headquarters of Airtel, an Indian telecom. It had only been open for a few weeks when I visited early last year. Bursts of fuchsia bougainvillea garlanded the entryway to the building, a welcome respite from the sand-colored landscape and sewage-infused scent of the rotting industrial district around it. One lot over sat a former Total gas station that has remained unbranded since a drug cartel bought it to launder money and removed the sign. Running across the zone was a boulevard commemorating a 1974 coup d’état, which has been followed by four more over the ensuing five decades, the latest in July 2023. In the middle of the boulevard sat a few dozen miles of decomposing railway tracks that had been “inaugurated” by a right-wing French billionaire in 2016. For decades, postcolonial elites, promising development, have pillaged one of Africa’s poorest countries.
In more recent years, various Western players touting tech trends like artificial intelligence and predictive analysis have swooped in with promises to solve the region’s myriad problems. But Garbal—named after the word for a livestock market in the language of the Fulani, an ethnic group that makes up the majority of the Sahel’s herders—aims to do things differently. Building on an approach pioneered by a 37-year-old American data scientist named Alex Orenstein, Garbal is focused on how humbler technologies might effectively support the 80% of Nigeriens who live off livestock and the land.
“There’s still this idea of ‘How can we use new tech?’ But the tech is already there—we just need to be more intentional in applying it,” Orenstein says, arguing that donor enthusiasm for shiny, complex solutions is often misplaced. “All of our big wins have come from taking some basic-ass shit and making it work.”
Workers in the Garbal call center in Niamey are able to review data to help herders.HANNAH RAE ARMSTRONG
Garbal’s work comes down to data and, critically, who should have access to it. Recent advances in data collection—both from geosatellites and from herders themselves—have generated an abundance of information on ground cover quantity and quality, water availability, rain forecasts, livestock concentrations, and more. The resulting breakthroughs in forecasting can, in theory, help people anticipate—and protect herds from—droughts and other crises. But Orenstein believes it is not enough to extract data from
By: Hannah Rae Armstrong
Title: Why shiny, high-tech solutions won’t solve one of Africa’s worst crises
Sourced From: www.technologyreview.com/2024/03/01/1089006/high-tech-solutions-garbal-call-centers-herding-conflict-africa-sahel/
Published Date: Fri, 01 Mar 2024 06:00:00 +0000
The Download: tech help for herders, and bacteria clean-ups
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.
Why shiny, high-tech solutions won’t solve one of Africa’s worst crises
Herding— one of humanity’s most foundational ways of life—is a pillar of survival in West Africa’s Sahel.
Migratory herders usher cattle between seasonal pastures, since they rarely own land. However, these traditional ways of doing things are becoming increasingly impossible, thanks to a complex mix of climate change, politics and war.
In more recent years, various Western players touting tech trends like artificial intelligence and predictive analysis have swooped in with promises to solve the region’s myriad problems.
But some think there could be a much simpler solution, that puts real data directly into the herders’ hands.
Recent advances in data collection—both from geosatellites and from herders themselves—have generated an abundance of information on ground cover quantity and quality, water availability, rain forecasts, livestock concentrations, and more. The resulting breakthroughs in forecasting could help people anticipate droughts and other crises.
The work couldn’t be more urgent. The region’s herders face an existential crisis that has already started to shred the very fabric of society. Read the full story.
—Hannah Rae Armstrong
How bacteria are cleaning up our messy water supply
Some bacteria are evolving in a way that could help, rather than hurt us. That’s good news, because the US has made a real mess of its water supply.
Scientists first detected pharmaceuticals in water more than 40 years ago. But concern has increased dramatically in the past 20 years, as a dizzying array of medications and personal care products swill into the water supply.
Luckily, there might be a way to tackle it: using bacteria which get rid of these tiny pollutants. Read our story to find out how.
This story is from The Checkup, our weekly newsletter all about biotech and health. Sign up to receive it in your inbox every Thursday.
I’ve combed the internet to find you today’s most fun/important/scary/fascinating stories about technology.
1 AI is unleashing a data center goldrush
It could rise from 2% of the global data center footprint to 10% by 2025. (NYT $)
AI’s carbon footprint is bigger than you think. (MIT Technology Review)
2 Emissions reached a record high in 2023
A big driver of that increase was extreme drought, which cut hydropower production in some countries. (Bloomberg $)
And forecasters predict we’re in for a very hot 2024. (The Verge)
ExxonMobil is suing investors who want quicker climate action. (NPR)
3 GoFundMe donations to campaigns in Gaza keep being frozen
Legitimate concerns over money laundering and terrorist financing are blocking desperate civilians from getting aid. (The Verge)
4 Can we control AI’s hallucinations?
It’s possible that we can’t. And in that scenario, it’ll remain risky to use AI for any important tasks. (The Economist $)
Google’s problem isn’t that its AI is ‘woke’. It’s that it’s being rushed out into products too quickly. (Bloomberg $)
The SEC is investigating whether OpenAI misled investors. (WSJ $)
Generative AI is challenging the very notion of copyright. (The Atlantic $)
Your posts are being used to train AI. Yes, even the ones you would imagine are safe. (Vox)
5 A humanoid robots startup got $675 million from tech investors
But can it really succeed where so many others have failed? (FT $)
6 More than one billion people now have obesity
It’s shocking how big this public health problem has become now. (Axios)
However, weight loss drugs are poised to potentially help alleviate it. (MIT Technology Review)
7 Conspiracists are obsessing over Kate Middleton online
These people seem to just have way too much time on their hands. (The Atlantic $)
8 The FBI is using push alerts to catch suspects
But it’s a privacy nightmare, and could include people seeking abortions. (WP $)
9 A viral photo of a guy smoking in McDonald’s was made by AI
There are ways to tell, but they’re tricky to spot at a glance. (Quartz)
10 Zuckerberg is having a bit of a PR moment
Enjoy it while it lasts, Mark. (Axios)
Quote of the day
“I’m totally 100%, sadly addicted to this.”
—Artist and musician Laurie Anderson tells The Guardian she can’t stop talking to an AI version of her late husband Lou Reed.
The big story
Inside the billion-dollar meeting for the mega-rich who want to live forever
By: Charlotte Jee
Title: The Download: tech help for herders, and bacteria clean-ups
Sourced From: www.technologyreview.com/2024/03/01/1089383/tech-help-herders-bacteria-clean-up/
Published Date: Fri, 01 Mar 2024 13:10:00 +0000
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