Adobe, once wary of how generative AI could disrupt its professional creative base, is now fully embracing the technology as a new frontier for augmented creativity. On Wednesday, the company announced it was taking its Firefly AI out of beta and rolling it out commercially across its Creative Cloud, Adobe Express, and Experience Cloud platforms.

As part of the rollout, Adobe launched a new Firefly web portal for AI experimentation, integrated Firefly capabilities directly into Photoshop and Illustrator, and added AI features to Express.

On Wednesday, Adobe announced it was taking its Firefly AI out of beta and rolling it out commercially across its Creative Cloud, Adobe Express, and Experience Cloud platforms.

Traditional semiconductor chip design typically begins with a lengthy and often arduous process of specification definition, RTL model creation and documentation, before engineering teams can set out on designing actual circuits. However, what if this IP creation and team-based design review phase could be cut down to a few weeks, rather than months, with literally hundreds of hours of design team meetings saved in the process?

This is the goal of a new “ChipGPT” type tool, that Cadence Design Systems is bringing to market, which employs Large Language Models and generative AI to do much of the heavy lifting in this early semiconductor definition and design verification phase.

As a new… More.

Generative AI has once again proven itself capable of alleviating semiconductor design teams from large portions of iterative optimization and verification work.

Large language model (LLM) AI chatbots may be able to outperform the average human at a creative thinking task where the participant devises alternative uses for everyday objects (an example of divergent thinking), suggests a study published in Scientific Reports. However, the human participants with the highest scores still outperformed the best chatbot responses.

Divergent thinking is a type of thought process commonly associated with creativity that involves generating many different ideas or solutions for a given task. It is commonly assessed with the Alternate Uses Task (AUT), in which participants are asked to come up with as many alternative uses for an everyday object as possible within a short time period. The responses are scored for four different categories: fluency, flexibility, originality, and elaboration.

Mika Koivisto and Simone Grassini compared 256 human participants’ responses with those of three AI chatbots’ (ChatGPT3, ChatGPT4, and Copy. Ai) to AUTs for four objects—a rope, a box, a pencil, and a candle. The authors assessed the originality of the responses by rating them on semantic distance (how closely related the response was to the object’s original use) and creativity.

Large language models are getting better at mimicking human creativity. That doesn’t mean they’re actually being creative, though.

AI is getting better at passing tests designed to measure human creativity. In a study published in Nature Scientific Reports today, AI chatbots achieved higher average scores than humans in the Alternate Uses Task, a test commonly used to assess this ability.

This study will add fuel to an ongoing debate among AI researchers about what it even means for a computer to pass tests devised for humans. The findings do not necessarily indicate that AIs are developing an ability to do something uniquely human. It could just be that AIs can pass creativity tests, not that… More.