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In an age of increasingly advanced robotics, one team has well and truly bucked the trend, instead finding inspiration within the pinhead-sized brain of a tiny flying insect in order to build a robot that can deftly avoid collisions with very little effort and energy expenditure.

An insect’s tiny brain is an unlikely source of biomimicry, but researchers from the University of Groningen in the Netherlands and Bielefeld University in Germany believed it was an ideal system to apply to how robots move. Fruit flies (Drosophila melanogaster) possess remarkably simple but effective navigational skills, using very little brainpower to swiftly travel along invisible straight lines, then adjusting accordingly – flying in a line angled to the left or the right – to avoid obstacles.

With such a tiny brain, the fruit fly has limited computational resources available to it while in flight – a biological model, the scientists believed, that could be adapted to use in the ‘brain’ of a robot for efficient, low-energy and obstacle-avoiding locomotion.

Dr. Richard Naud’s research at the University of Ottawa holds important implications for understanding learning and memory theories, and it may pave the way for advancements in artificial intelligence in the future.

The mysteries of the human brain’s internal mechanisms are slowly being uncovered, and a significant new study led by Dr. Richard Naud from the Faculty of Medicine at the University of Ottawa is bringing us nearer to solving these profound questions.

The study’s results have important implications for theories of learning and working memory and could potentially help lead to future developments in artificial intelligence (AI) since AI developers and programmers watch the work of Dr. Naud and other leading neuroscientists.

The H3’s main missions are to secure independent access to space and be competitive as international demand for satellite launches grows. “We made a big first step today toward achieving that goal,” Yamakawa said.

The launch is a boost for Japan’s space program following a recent streak of successes, including a historic precision touchdown on the moon of an unmanned spacecraft last month.

The liftoff was closely watched as a test for Japan’s space development after H3, in its debut flight last March, failed to ignite the second-stage engine. JAXA and its main contractor Mitsubishi Heavy Industries have been developing H3 as a successor to its current mainstay, H-2A, which is set to retire after two more flights.

Spilling your hopes, secrets, and fantasies to your AI girlfriend? You might want to reconsider.

In a new report, experts at the Mozilla Foundation warn that AI companion bots — including the popular app Replika — are plagued by deeply concerning privacy pitfalls and murky data use policies.

“So-called ‘AI soulmates’ are giving Mozilla the ick when it comes to how much personal information they collect,” reads the Mozilla report, “especially given the lack of transparency and user control over how this data is protected from abuse.”

ChatGPT maker OpenAI stepped up the race in generative artificial intelligence Thursday when it unveiled its text-to-video generation tool, Sora, viewed as an impressive but potentially dangerous step in the booming AI economy amid concerns about disinformation spread.


“Game on,” said the CEO and cofounder of rival video generator Runway after OpenAI teased content from its latest AI tool.

The human brain is probably the most complex thing in the universe. Apart from the human brain, no other system can automatically acquire new information and learn new skills, perform multimodal collaborative perception and information memory processing, make effective decisions in complex environments, and work stably with low power consumption. In this way, brain-inspired research can greatly advance the development of a new generation of artificial intelligence (AI) technologies.

Powered by new machine learning algorithms, effective large-scale labeled datasets, and superior computing power, AI programs have surpassed humans in speed and accuracy on certain tasks. However, most of the existing AI systems solve practical tasks from a computational perspective, eschewing most neuroscientific details, and tending to brute force optimization and large amounts of input data, making the implemented intelligent systems only suitable for solving specific types of problems. The long-term goal of brain-inspired intelligence research is to realize a general intelligent system. The main task is to integrate the understanding of multi-scale structure of the human brain and its information processing mechanisms, and build a cognitive brain computing model that simulates the cognitive function of the brain.