With the ease of availability and access of AI tools and technology, people are putting AI into a wide range of products and services, and even in applications where AI is a dubious fit, at best. Many times, organizations are feeling the motivation, “fear of missing out”, and perhaps customer or shareholder pressure to add AI capability to their offerings. It should come as no surprise that many of these AI projects are often half thought-out, at best, and often fail to deliver the desired results, if the results have even been considered ahead of time.

Sometimes, AI projects have a high-level, big vision, where the AI efforts are focused. Other times, AI applications are being focused on smaller tasks, or shoehorned into existing applications. The challenge is that for AI projects to be successful, there needs to be a combination of a larger vision for where AI could add value while at the same time, smaller, focused projects that allow organizations to ensure value in the real-world before diving deeper into AI capabilities and investment.

Dive into Yann LeCun’s perspective on the shortcomings of generative AI and his advocacy for Objective-Driven AI, offering a transformative approach.

The latest scandal involves a Google engineer accused of stealing AI secrets.

Taichi could potentially make artificial general intelligence a reality.

Researchers at Tsinghua University in China have developed a revolutionary new artificial intelligence (AI) chip that uses light instead of electricity to process data.

Researchers have developed a highly energy-efficient photonic AI chip called Taichi, which could accelerate the development of advanced computing solutions.

The highest-level Hidra chip will power Apple’s highest-end desktop, the Mac Pro. To give you an idea of how powerful the chip might be, Apple is working to support the Mac Pro with 512 GB RAM. Unlike Intel’s processor, which allows additional memory to be added later, Apple Silicon is more deeply integrated into the processor, and therefore, the RAM options will have come from Apple itself.

With the M4 chip nearing production, Apple could unveil its new and updated Mac lineup later this year and follow it up with releases through 2025, the Bloomberg report added.

A newer lineup also gives the Cupertino-based company an opportunity to join the league of tech giants working on AI. Compared to Microsoft and Google, which have already released their AI-powered products, Apple has been a laggard in the AI space.

The design is intended to provide more computing power, bandwidth, and memory capacity to the chips. Initially, Meta aimed to perform inference functions such as ranking and generating responses to user prompts. Meta plans to use the chips for more intense operations, such as training AI models using large data sets.

A shift to its chips could help Meta save millions in energy costs every year, alongside the billions needed in capital expenditure to buy chips from Nvidia.

Meta isn’t the only tech company looking to design and build its own AI chips. Legacy chipmaker Intel, which has lagged in catering to industry requirements for AI chips, also announced its new Gaudi chips at an event on Tuesday.