What does a crisis in the global economy mean for Artificial Intelligence? This is a question we are frequently asked in the face of a collapse in public market valuations for many growth-oriented tech stocks, rising inflation and interest rates combined with tightened monetary policy, supply chain disruptions resulting from the war in Ukraine and ongoing pandemic lockdowns in China, and the strong possibility of a resulting global recession.
We hope to soon see the end of the pandemic and war, the easing of inflation, and a soft landing for the economy. In the meantime, to survive and thrive, companies will be forced to focus on higher productivity and better margins. However, businesses face the additional challenge of historically low unemployment.
Some industries have many more jobs open than there are people to fill them. This is especially acute throughout the supply chain (often in lower-paying jobs with repetitive tasks such as in manufacturing, pick/pack/ship warehouses, and farm-picking), long-haul driving, and healthcare and elderly care workers. This paucity of available workers is further exacerbated by political, demographic, and health issues, including: (1) restrictive immigration policies, (2) pandemic illness, (3) an aging population in much of the world outside of many African countries, and (4) de-globalization and the on-shoring of manufacturing and supply chains.
In the absence of more workers (which seems unlikely in the US given prevailing political winds vis-a-vis immigration), one solution is to pay more to entice workers into the job market. This, of course, results in lower margins or higher-priced goods and services, or some combination of the two.
Another solution presents an opportunity: adopting technologies that simultaneously reduce costs and, unlike previous generations of technology, continuously improve quality and productivity by self-learning following the initial deployment. That is exactly what AI does and is why we believe the next 10+ years will see an extraordinary acceleration in the adoption of AI, including AI software and AI-enabled semiconductors and ‘smart’ robots, across nearly every industry.
So, while global political and economic developments may seem grim, every day we are seeing new technologies that promise to make the world a much better place. That is reflected in Radical Ventures’ portfolio of companies, which have developed the technology infrastructures and solutions that can help lead to a happier and healthier future for everyone.
AI News This Week
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The big new idea for making self-driving cars that can go anywhere (MIT Technology Review)
World-leading machine learning and computer vision expert Raquel Urtasun founded Radical Ventures portfolio company Waabi to pioneer self-driving technology. Her goal has been to unleash the full power of AI to ‘drive’ safely in the real world. This year the company released Waabi World, a scalable, immersive and reactive environment powered by AI that can design tests, assess skills, and teach the self-driving ‘brain’ to learn to drive on its own. Other autonomous vehicle startups also recognize the enormous success of reinforcement learning and are turning to an AI-based approach in their work. In the article, Raquel noted, “There is way too much overselling in this field. There’s also a lack of acknowledgment of how difficult the task is in the first place. But I don’t believe that the mainstream approach to self-driving is going to get us to where we need to be to deploy the technology safely.”
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How machine learning is transforming biotech research (The Logic – subscription required)
AI is transforming the drug discovery and development process as biotech researchers are using computational methods to predict and test potential drug candidates. Featured in the article is Radical Ventures portfolio company Genesis Therapeutics, a company spun out of the Pande Lab at Stanford, pioneering AI technologies to create medicines for patients with severe and unmet medical conditions. The company recently announced a collaboration with Eli Lilly to discover novel therapies for up to five targets across a range of therapeutic areas. Radical Ventures Partner Rob Toews is quoted in the article, “There may be no category where AI has a larger impact over the long term than in bio[tech].”
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Quantum Internet’ inches closer with advance in data teleportation (The New York Times – subscription may be required)
Ronald Hanson, a physicist at the QuTech laboratory at Delft University in the Netherlands, and his team recently published a paper in Nature demonstrating the first steps toward qubit teleportation. The researchers were able to send data across three physical locations. Previously, Hanson’s team and others showed it was possible with only two points. The third point indicates that scientists can stretch a quantum network across an increasingly large number of sites. However, the physicist notes that further improvements in multiple system features will be needed to enable multiple rounds of teleportation – what is required to achieve a quantum internet. If achieved, computers on the quantum web could carry out tasks within minutes that would take today’s supercomputers thousands of years to execute.
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Minecraft’s self-coding NPC points to the future of computers (Wired)
A new ‘self-coding’ nonplayer character (NPC) in Minecraft may reveal new ways we can think about personal computing. The same AI used for GitHub Copilot, a tool for auto-generating software code, powers the help character. The NPS responds to typed commands by converting them into working code behind the scenes using the software API for the game. For example, “Tell the agent to ‘come here,’ and the underlying artificial intelligence model will generate the code to have the agent move in the player’s direction.” Some view this as a step toward the death of manual interface hardware, replacing tapping, typing, and clicking with conversation.
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This bacterial disease can be deadly for your pet. UC Davis is using AI to catch it early (The Sacramento Bee)
University of California, Davis researchers created an AI model that predicts if a dog has the bacterial disease leptospirosis – a potentially life-threatening bacterial infection. Dogs can get the disease by drinking from puddles or bodies of water that carry urine from infected wildlife. Early detection is critical, yet tests currently lack sensitivity taking up to two weeks for results. While the model has only demonstrated an ability to confirm dogs that are already positive, uncovering underlying patterns in the tests may speed up detection and get more information out of costly lab tests.
Radical Reads is edited by Leah Morris (Senior Director, Velocity Program, Radical Ventures).