Lifeboat Foundation: Safeguarding Humanity
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Around 38% of the world’s total landmass is used for agriculture – yet hunger is worsening, and food security is in crisis, threatened by pressures including climate change, conflict and global recessions.

While there’s no one-stop solution, technology can help to fill some of the gaps. Mechanical engineer Josie Hughes is on a mission to show how robotics can play a role in our everyday lives, particularly when it comes to food. Starting with LEGO robots as a child, the Cambridge graduate now leads the Computational Robot Design & Fabrication Lab (CREATE) at the Swiss Federal Institute of Technology Lausanne (EPFL), where she’s one of the youngest researchers to join as a tenure-track assistant professor.

One of her innovations, a raspberry-picking robot powered by artificial intelligence, could help make farming more efficient and cost-effective, and solve labor shortages – which in the UK alone left £60 million ($74 million) worth of fruit and vegetables rotting in fields this summer. CNN spoke with Hughes about her research, and when robots might be harvesting your next meal.

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Check out all the on-demand sessions from the Intelligent Security Summit here.

The adoption of a password-free future is hyped by some of the biggest tech companies, with Apple, Google, and Microsoft committing to support the FIDO standard this past May. Along with the Digital ID Bill reintroduced to Congress this past July, we’re poised to take a giant leap away from the password to a seemingly more secure digital future. But as we approach a post-password world, we still have a long way to go in ensuring the security of our digital lives.

As companies continue developing solutions to bridge us to a passwordless world, many have prioritized convenience over security. Methods of two-factor authentication (2FA) and multi-factor authentication (MFA) such as SMS or email verification — or even the use of biometrics — have emerged as leading alternatives to the traditional username/password. But here’s the catch: Most of these companies are validating devices alone and aren’t properly leveraging this technology, leaving the door open for bad actors.

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A gene therapy gel for a blistering skin disease developed at Stanford Medicine has worked wonders in a double-blind, placebo-controlled clinical trial.

The gel, called B-VEC, was intended to treat dystrophic epidermolysis bullosa, a skin disease that results in large open wounds that last for decades. The condition is extremely painful, and the medical treatment is mostly limited to palliative care.

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Apple is working on an online search engine to rival Google amid wider improvements to Spotlight search, according to a recent report from The Information.

The report explains that Apple’s work on search technology is facing setbacks amid a loss of talent to Google. In 2018, Apple sought to bolster development of its own web search engine by buying machine learning startup Laserlike, which was founded by three former Google search engineers. The company’s technology recommended websites based on a user’s interests and browsing history. Now, Laserlike’s founders have reportedly returned to Google.

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Following Musk’s decision to fire top executives and appoint himself CEO in October, Bloomberg reported that the billionaire likely planned to serve in the role on an interim basis.

In the replies to the tweet, Musk said he had not selected a replacement, after a user suggested he had already chosen one.

“No one wants the job who can actually keep Twitter alive. There is no successor,” Musk tweeted.

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How programmers turned the internet into a paintbrush. DALL-E 2, Midjourney, Imagen, explained.

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Beginning in January 2021, advances in AI research have produced a plethora of deep-learning models capable of generating original images from simple text prompts, effectively extending the human imagination. Researchers at OpenAI, Google, Facebook, and others have developed text-to-image tools that they have not yet released to the public, and similar models have proliferated online in the open-source arena and at smaller companies like Midjourney.

These tools represent a massive cultural shift because they remove the requirement for technical labor from the process of image-making. Instead, they select for creative ideation, skillful use of language, and curatorial taste. The ultimate consequences are difficult to predict, but — like the invention of the camera, and the digital camera thereafter — these algorithms herald a new, democratized form of expression that will commence another explosion in the volume of imagery produced by humans. But, like other automated systems trained on historical data and internet images, they also come with risks that have not been resolved.

Continue reading “The text-to-image revolution, explained” | >