After 23 years, millions of dollars and numerous filmmakers coming and going, Warner Bros has failed to make Akira happen.

Trying to bring what is widely regarded as one of the greatest animes ever made into the real world is no easy task, so much ...

After 20 years, a dozen creatives attached and millions spent on development, Warners is moving on from the seminal property.

(“Turning into an Akira” is a reference in itself). Set in a dystopian 2019, the story follows Kaneda (Mitsuo Iwata), the leader of a biker gang, whose friend Tetsuo (Nozomu Sasaki) gains ...

Akira Kurosawa‘s legacy is getting the 4K treatment with a massive U.S. festival. Film Forum in New York City will be hosting a special retrospective to honor the late auteur, including the U.S ...

POM Anime unveils 2025 slate with 'Akira' 4K restoration, 'Dan Da Dan' sequel, 'Grave of the Fireflies' and 'Lupin' across 20+ European territories.

Technology AI hallucinations are getting worse – and they're here to stay An AI leaderboard suggests the newest reasoning models used in chatbots are producing less accurate results because of ...

Hallucinations and their effects depend on the type of AI system. With large language models, hallucinations are pieces of information that sound convincing but are incorrect, made up or irrelevant.

They can even be life-threatening: Autonomous vehicles use AI to detect obstacles, other vehicles and pedestrians. Making it up Hallucinations and their effects depend on the type of AI system.

Serving tech enthusiasts for over 25 years. TechSpot means tech analysis and advice you can trust. In context: Akira is a dangerous, multiplatform ransomware threat that has been active since 2023.

Akira ransomware dynamically generates unique encryption keys for each file using four different timestamp seeds with nanosecond precision and hashes through 1,500 rounds of SHA-256.

AI hallucinations can be compared with how humans perceive shapes in clouds or faces on the moon. These misinterpretations arise due to factors such as overfitting, bias, inaccuracies in the ...