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We’ve highlighted a lot of bright innovators over the years, usually before they become household names. Sergey Brin of Google was on the list in 2002. JB Straubel was honored in 2008 when he was CTO of Tesla. That year also saw Andrew Ng make the list (he’s one of the biggest names in AI right now, and he came back this year to write an intro essay, which I highly recommend.)

As I looked through the folks who made the list in the climate and energy category in 2023, I noticed a few trends. In particular, there was a concentration in two areas I think a lot about: batteries and fuels. So let’s take a closer look at a few of this year’s innovators and consider what their work could mean for the future of climate action.

As you probably know if you’re a frequent reader here, I see batteries as one of the most crucial pieces of technology in the fight to address climate change. Not only are powerful, long-lasting batteries crucial to electrifying vehicles and other forms of transportation, but they are expected to play a growing role on the grid, storing energy from intermittent renewable sources like wind and solar for when it’s most needed.

As instructors settle into a new academic year, AI technologies like ChatGPT offer new dimensions for teaching and student engagement. While the allure of AI is captivating, the chatbots are still in their formative stages and thus imperfect, sometimes producing a mix of facts and fiction and raising an array of questions about academic integrity.

Many higher education institutions have recently changed their stances on the tools, from banning them last spring to allowing instructors to use the technology in their classes this fall. While the overwhelming majority of higher education institutions lack formal policies on the use of AI, according to research by Tayton Partners, some have… More.


Opportunities and challenges AI presents in academia, and how educators can navigate this emerging landscape. Discussing guides offered by OpenAI and universities.

The 30-minute flight was operated by Dronery using Ehang’s EH216-S aircraft.

In a first, an eVTOL (Electric Vertical Take-off and Landing) aircraft flew over Jerusalem, which takes Israel to the verge of opening up its airspace to air taxi providers.

The experimental flight was part of Israel’s Israel National Drone Initiative (INDI), which attempts to create a network of drones to provide transportation services and reduce traffic congestion in its cities. The project focuses on laying a foundation for a flying car/sky taxi sector and operations based on eVTOL technologies.

Japanese researchers hope that a made-in-Japan AI chatbot could help to accelerate science.

Best known for automobiles and consumer electronics, Japan has fallen behind on recent technology trends like artificial intelligence. Its scientists believe that as the country’s population shrinks, Japan will have a strong incentive to make great leaps in AI and robotics to maintain productivity.

Although ChatGPT is being used by Japanese municipalities to carry out governmental work, Japanese scientists say that the country needs to come up with its own version of ChatGPT.

Our hope is for COVID-19 to never repeat itself,’ said the new program’s executive director.

A program run by a Canadian university is seeking to improve global health care for the most vulnerable by examining how artificial intelligence (AI) can enhance readiness for infectious disease epidemics in the Global South.

This is according to a report by CTV News published on Wednesday.


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Microsoft AI researchers accidentally exposed tens of terabytes of sensitive data, including private keys and passwords, while publishing a storage bucket of open source training data on GitHub.

In research shared with TechCrunch, cloud security startup Wiz said it discovered a GitHub repository belonging to Microsoft’s AI research division as part of its ongoing work into the accidental exposure of cloud-hosted data.

Readers of the GitHub repository, which provided open source code and AI models for image recognition, were instructed to download the models from an Azure Storage URL. However, Wiz found that this URL was configured to grant permissions on the entire storage account, exposing additional private data by mistake.

Humanoid robots are pretty cool, and Agility Robotics‘bipedal robot Digit is up there in terms of advanced tech (it even has a face!). Today, the company announced it’s getting ready to crank up its RoboFab, which can build more than 10,000 Digits per year. Obvious Skynet jokes aside, I, for one, welcome our new robotic overlords.

The factory will be built in Salem, Oregon, and the company tells TechCrunch it started initial construction of the 70,000-square-foot robot factory last year, and it is set to open later this year.

“The opening of our factory marks a pivotal moment in the history of robotics: the beginning of the mass production of commercial humanoid robots,” said Agility Robotics’ co-founder and CEO Damion Shelton. “We built Digit to solve difficult problems in today’s workforce like injuries, burnout, high turnover and unfillable labor gaps, with the ultimate vision of enabling humans to be more human. When you’re building new technology to make society better, the most important milestone is when you’re able to mass produce that technology at a scale where it can have a real, widespread impact.”

By regularly patrolling the property, armed guards prevent potential crimes simply by being present. Security patrols involve reviewing and monitoring the premises to ensure they are safe from potential threats.

However, foot patrol guards travel slowly and carry limited equipment. Due to this, the guard’s range and area coverage are relatively restricted. Patrolling guards also need help to do their duty in harsh weather conditions.

A Swiss Security and Investigations company, Ascento, has unveiled their new autonomous security patrolling robot, Ascento Guard.

Artificial intelligence (AI) refers to complex software that performs tasks in a way similar to human brains, often by sensing and responding to a feature of their environment. This could mean learning to solve problems in unexpected ways, recognising the nuances of speech, or exhibiting some form of human-like creativity.

Just as no single quality defines human thinking, no clear line differentiates more basic computer programs from AI. It can be thought of more as an ideal than a category — using our own penchant for learning and problem solving to inspire new technology and answers to some of our biggest and most complex questions.

There are many different fields of AI, including ’robotics’, but one of the most commonly known forms is referred to as ‘machine learning’. This involves a program applying known information to new experiences and ‘learning’ how to take this historical information and its experiences into account in future actions.

At a glance, Gemini’s ability to generate text and images gives it a serious advantage over GPT4 with respect to the range of content that it can produce.

However, perhaps the most threatening differentiator between the two is Google’s vast array of proprietary training data. Google Gemini can process data taken across services, including Google Search, YouTube, Google Books, and Google Scholar.

The use of this proprietary data in training the Gemini models could result in a distinct edge in the sophistication of the insights and inferences that it can take from a data set. This is particularly true if early reports that Gemini is trained on twice as many tokens as GPT4 are correct.


The launch of ChatGPT last November shook Google to its foundations. The popular chatbot posed such a threat to the company’s business that it had to declare a code red and began investing in catching up on the generative AI bandwagon. This effort has not only resulted in the release of Google Bard but also Gemini.