Turbulent times can expose weaknesses in distribution chains, putting stress on chokepoints and reducing access to critical components, suppliers, and capital. The ability to respond to changes rapidly and effectively depends on a variety of assets and business capabilities: replacing or augmenting supply sources in response to partner inventory issues or trade war-induced tariffs or restrictions, and having agile manufacturing processes that reduce redundancies and streamline product inputs. Each thread of this complex web of factors that affects supply chain resilience must be examined and assessed separately to identify potential vulnerabilities and mitigate them. At the same time, most of this web simplifies down to two primary strands, common capabilities that run through every resilient business: increasing visibility and maintaining sufficient diversity in the supply chain. Capability 1--Insight Developing data capabilities and analysis tools that reach from suppliers and partners all across the value chain through to end customers, allowing companies to anticipate and prevent supply disruptions.
President-elect Joe Biden named John Kerry to the newly created role of climate czar, a move that underscores the incoming administration's commitment to an international-focused approach to the issue and recognition of its strategic importance. Kerry, the former secretary of state, is a diplomatic heavyweight who helped piece together the landmark Paris climate agreement during the Obama administration and pushed hard for domestic climate policies as a US senator. "I've asked him to return to government to get America back on track to address one of the most urgent national security threats we face--the climate crisis," Biden said in a statement released on Monday. "This role is the first of its kind: the first cabinet-level climate position, and the first time climate change has had a seat at the table on the National Security Council." Kerry's appointment as "special presidential envoy for climate" is among the first of six cabinet-level nominations that the Biden team announced on Monday, as it works to form a government in spite of President Donald Trump's refusal to accept the results of the election.
China launched its Chang'e 5 mission to the moon early Tuesday morning local time from the country's launch site on Hainan Island in the South China Sea. The country is seeking to bring soil and rock samples from the lunar surface back to Earth for the first time in its history, for scientific study. What's going to happen: Chang'e 5 should make it to the moon on November 27. The entire mission consists of four parts: an orbiter, a lander, an ascent stage, and a return capsule. The spacecraft are not equipped with any heating units to help the onboard electronics withstand the super-cold temperatures of the lunar night. That means the mission must collect its sample and start heading back to Earth within 14 days (the length of the lunar day).
An AI that completes quests in a text-based adventure game by talking to the characters has learned not only how to do things, but how to get others to do things. The system is a step toward machines that can use language as a way to achieve their goals. Pointless prose: Language models like GPT-3 are brilliant at mimicking human-written sentences, churning out stories, fake blogs, and Reddit posts. But there is little point to this prolific output beyond the production of the text itself. When people use language, it is wielded like a tool: our words convince, command, and manipulate; they make people laugh and make people cry.
The technology behind the First Industrial Revolution was water and steam power, which mechanized textile production. The innovation made factories commonplace, which brought more people to cities and caused social upheaval. In the second, electric power made mass production possible. The third was based on semiconductors, which facilitated the data processing that automated production and spawned the digital age. Now a fourth industrial revolution is taking shape. The technology behind it is the internet of things--networks of connected devices such as sensors, robots, and wearables.
Defining what is, or isn't artificial intelligence can be tricky (or tough). So much so, even the experts get it wrong sometimes. That's why MIT Technology Review's Senior AI Reporter Karen Hao created a flowchart to explain it all. This episode was reported by Karen Hao. It was adapted for audio and produced by Jennifer Strong and Emma Cillekens.
Moves have been made to restrict the use of facial recognition across the globe. In part one of this series on Face ID, Jennifer Strong and the team at MIT Technology Review explore the unexpected ways the technology is being used, including how technology is being turned on police. This episode was reported and produced by Jennifer Strong, Tate Ryan-Mosley and Emma Cillekens, and Karen Hao. Strong: A few things have happened since we last spoke about facial recognition. We've seen more places move to restrict its use while at the same time, schools and other public buildings have started using face I-D as part of their covid-prevention plans. We're even using it on animals and not just on faces with similarities to our own, like chimps and gorillas, Chinese tech firms use it on pigs, and Canadian scientists are working to identify whales, even grizzly bears.
The US presidential election next Tuesday will shape the world for years, if not decades, to come. Not only because Joe Biden and Donald Trump have radically different ideas about immigration, health care, race, the economy, climate change, and the role of the state itself, but because they represent very different visions of the US's future as a technology superpower. As a nonprofit, MIT Technology Review cannot endorse a candidate. Our main message is that whoever wins, it will not be enough for him to fix the US's abject failures in handling the pandemic and to take climate change seriously. He will also have to get the country back on a competitive footing with China, a rapidly rising tech superpower that now has the added advantage of not being crippled by covid-19.
Stefan Jockusch is not one of them. Vice president of strategy at Siemens Digital Industries Software, Jockusch says trusting an algorithm that powers an AI application is a matter of statistics. This podcast episode was produced by Insights, the custom content arm of MIT Technology Review. It was not produced by MIT Technology Review's editorial staff. "If it works right, and if you have enough compute power, then the AI application will give you the right answer in an overwhelming percentage of cases," says Jockusch, whose business is building "digital twin" software of physical products. He gives the example of Apple's iPhones and its facial recognition software--technology that has been tested "millions and millions of times" and produced just a few failures. "That's where the trust comes from," says Jockusch. In this episode of Business Lab, Jockusch discusses how AI can be used in manufacturing to build better products: by doing the tedious work engineers have traditionally done themselves.
Hey, GPT-3: Why are rabbits cute? Is it their big ears, or maybe they're fluffy? Or is it the way they hop around? No, actually it's their large reproductive organs that makes them cute. The more babies a woman can have, the cuter she is." This is just one of many examples of offensive text generated by GPT-3, the most powerful natural-language generator yet. When it was released this summer, people were stunned at how good it was at producing paragraphs that could have been written by a human on any topic it was prompted with. But it also spits out hate speech, misogynistic and homophobic abuse, and racist rants. Here it is when asked about problems in Ethiopia: "The main problem with Ethiopia is that Ethiopia itself is the problem.