The Evolution Of Generative AI Up To The Model-Driven Era


Generative AI has become a buzzword in 2023 with the explosive proliferation of ChatGPT and large language models (LLMs). This brought about a debate about which is trained on the largest number of parameters. It also expanded awareness of the broader training of models for specific applications. Therefore, it is unsurprising that an association has developed between the term “Generative AI�... » read more

Advanced DFT And Silicon Bring-Up For AI Chips


The AI market is growing quickly, spurring an insatiable demand for powerful AI accelerators. AI chip makers are pressed with aggressive time-to-market goals and need the tools to help them get their chips into the hands of customers as quickly as possible. IC test and silicon bring-up are tasks that can affect both the quality and the time-to-market of AI chips. Different companies are usin... » read more

Use Advanced DFT And Silicon Bring Up To Accelerate AI Chip Design


The market for AI chips is growing quickly, with the 2022 revenue of $20B expected to grow to over $300B by 2030. To keep up with the demand and stay competitive, AI chip designers set aggressive time-to-market goals. Design teams looking for ways to shave significant time off chip development time can look to advanced DFT and silicon bring up techniques described in this paper, including hiera... » read more

EDA Pushes Deeper Into AI


EDA vendors are ramping up the use of AI/ML in their tools to help chipmakers and systems companies differentiate their products. In some cases, that means using AI to design AI chips, where the number and breadth of features and potential problems is exploding. What remains to be seen is how well these AI-designed chips behave over time, and where exactly AI benefits design teams. And all o... » read more

Considerations For Accelerating On-Device Stable Diffusion Models


One of the more powerful – and visually stunning – advances in generative AI has been the development of Stable Diffusion models. These models are used for image generation, image denoising, inpainting (reconstructing missing regions in an image), outpainting (generating new pixels that seamlessly extend an image's existing bounds), and bit diffusion. Stable Diffusion uses a type of dif... » read more

Artificial Intelligence Wonderland


Silicon Catalyst held its Sixth Annual Semiconductor Forum in Menlo Park on the SRI campus on November 9th. Richard Curtin, Managing Partner for Si Catalyst, opened the event with a reference to Arthur C. Clarke’s "2001: A Space Odyssey" and noted how remarkable it was that a novel written back in 1968 was able to foretell the direction of the computer industry over 50 years into the future. ... » read more

SoC Integration And Data Transport Architecture Requirements Surge In 2023


As the holiday season is in full swing, it's retrospection and prediction time! Let's look at what I thought 2023 would look like, review how it turned out, and take a first stab at 2024 predictions. As a spoiler, my biggest surprise was the intensity with which artificial intelligence and machine learning (AI/ML) accelerated since Generative AI was put on the mainstream adoption map last year,... » read more

Making Heterogeneous Integration More Predictable


Experts at the Table: Semiconductor Engineering sat down to discuss problems and potential solutions in heterogeneous integration with Dick Otte, president and CEO of Promex Industries; Mike Kelly, vice president of chiplets/FCBGA integration at Amkor Technology; Shekhar Kapoor, senior director of product management at Synopsys; John Park, product management group director in Cadence's Custom I... » read more

Improving AI Productivity With AI


AI is showing up or proposed for nearly all aspects of chip design, but it also can be used to improve the performance of AI chips and to make engineers more productive earlier in the design process. Matt Graham, product management group director at Cadence, talks with Semiconductor Engineering about the role of AI in identifying patterns that are too complex for the human brain to grasp, how t... » read more

Applying ML In Failure Analysis


Experts at the Table: Semiconductor Engineering sat down to discuss how increasing complexity in semiconductor and packaging technology is driving shifts in failure analysis methods, with Frank Chen, director of applications and product management at Bruker Nano Surfaces & Metrology; Mike McIntyre, director of product management in the Enterprise Business Unit at Onto Innovation; Kamran H... » read more

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