published by Semico_Admin on Wed, 2023-02-22 20:38
Principal Analyst Rich Wawrzyniak participated in a webinar hosted by Achronix, titled The Rise of the Chiplet. The webinar took place on February 9, 2023 and was moderated by SemiEngineering’s Brian Bailey. The panel members were Achronix’s Nick Ilyadis, Semico’s Rich Wawrzyniak, and ODSA’s Bapi Vinnakota. They discussed the current landscape for chiplet technology, predictions for the coming years, what’s needed for chiplet adoption, and the status and evolution of die-to-die interface standards, as well as answered live questions.
On Monday, February 7, 2022, Intel Foundry Services (IFS), made a series of major announcements regarding the RISC-V architecture and ecosystem:
What is the Real Promise of
Artificial Intelligence?
And Where Does BrainChip Fit into
the Picture?
Past and Present Technological Innovations
Unquestionably, the introduction of augmented Artificial Intelligence (AI) into our economy and society is going to have profound effects on how we engage with the world around us and how we expect the world to engage with us. Many parallels can be drawn between today’s AI innovations and similar past periods in history. In each of these cases, the world experienced great leaps in innovation and invention, which correspondingly produced great improvements in our daily lives.
Perhaps one of the most notable technological introductions was that of the mainframe computer for business and science applications back in the early 1950’s by IBM. This innovation led to the deployment of computing power to many companies throughout the world and allowed even small companies, through time-sharing arrangements, to have access to this capability. The 1950s and 1960s were decades where great leaps in productivity were made, enabled by this and other advancements.
Semico recently published an article in our March, 2021 IPI Newsletter detailing a press release between NaNose (Nano Artificial Nose) Medical and BrainChip in which they jointly announced a new system for medical diagnosis COVID-19. This system used an artificially intelligent nano-array based on molecularly modified gold nanoparticles and a random network of single-walled carbon nanotubes paired with the Akida neuromorphic AI processor from BrainChip.
Using a non-invasive breathalyzer approach, this system collects Volatile Organic Chemicals (VOC’s) given off by long list of diseases and passes these chemicals past the AI nano-array sensor and used the Akida neuromorphic processor to analyze the data, giving the results almost immediately with 86% accuracy.
Each of these technologies is projected to have great positive impacts on our society and economies in the near future. How much better then to detail the marriage of metamaterials and AI in this system as an impressive first step in that direction. In addition to the great achievement of being able to detect the COVID-19 virus non-invasively, this technology pairing can also detect a range of other diseases simultaneously with similar results.
The table below shows the other diseases that are detectable by the nano-array sensor and the BrainChip neuromorphic AI processor.
List of Diseases Detected by NaNose Medical Nano-array Sensor
On September 13, 2020, NVIDIA announced it had signed a definitive agreement to acquire Arm Holdings from SoftBank for $40 billion in a combination of NVIDIA stock and cash. SoftBank will retain a 10% interest in Arm. While there are regulatory issues to be resolved in the UK, the US and China, NVIDIA anticipates this process will take 12 to 18 months. The process of integrating the two companies will not start until the deal is consummated.
The Basics of the Acquisition
On June 23rd, 2020, Siemens AG signed a letter of intent to acquire Cambridge, UK-based 3rd Party Semiconductor Intellectual Property (SIP) vendor, UltraSoC. Terms of the transaction were not disclosed except to say Siemens plans to integrate UltraSoC’s technology into the Xcelerator portfolio as part of Mentor’s Tessent™ software product suite. The acquisition is expected to close in Siemens 4th fiscal quarter this year.
There are several areas where this acquisition is impactful to the SIP market, the EDA market and the broader semiconductor market.
SIP Market Impacts:
This week, Facebook announced it had acquired Sonics, Inc., a 3rd Party Semiconductor Intellectual Property (SIP) vendor. Sonics is one of the mainstays of the SIP market for Interconnect SIP, which is used to tie together the multiple tens or hundreds of SIP blocks found on contemporary System-on-a-Chip (SoC) silicon solutions today. Sonics was founded in 1996 and was at the heart of the emerging SoC market in its early years along with ARC, ARM, MIPS, Analog Bits, Virage Logic and many others.
It is no surprise that a company like Facebook, who is designing their own AI-focused SoCs, would purchase a company like Sonics. While no details of this acquisition have been released, some reasoned insights are possible.
Implications for the Market
This acquisition removes a major player for Interconnect SIP from the market. Sonics’ customers must now determine how long Sonics will support them and at what level. It is reasonable to expect these customers will look to other suppliers for their interconnect requirements.
The World Semiconductor Trade Statistics (WSTS) organization held its bi-annual forecast meeting in Scottsdale, Arizona last month, and one of the topics that seemed to be on everyone’s mind is the impact of tariffs and the trade tensions between the United States and China. The presentation with the most insightful information on this topic was provided by Falan Yinug, Director, Industry Statistics and Economic Policy, at the Semiconductor Industry Association (SIA).
The need to impose tariffs on U.S. imports of semiconductors is perplexing because as of 2017 the United States maintained a semiconductor trade surplus of $2.1 billion with China. In addition, most of the U.S. imports of semiconductors from China are products from U.S. semiconductor companies that are either designed and/or have undergone front-end fabrication outside of China.
Many IoT (Internet of Things) applications will be untethered, not connected by physical wires for power or communications. They will use batteries, and battery life will be critical. Atmosic Technologies, a Bay Area startup of ultra-low power wireless for the IoT, has developed a chip ideally suited for these applications.
This week, Atmosic Technologies launched the M2 and M3 series, touting it as the industry’s lowest-power wireless Bluetooth 5.0 chips. It offers improved battery life in three ways. First, the chip was designed from the ground up to be a low-power chip. It has intrinsic design features that offer five to 10 times more battery life than other Bluetooth 5.0 chips. Second, it has on-demand receiving. The chip can be in a sleep mode until it receives a Bluetooth signal including specific codes to wake it up. That feature can improve battery life by up to 100 times. Third, it includes an RF Power Harvesting Section. By harvesting RF energy, the chip offers what can be essentially infinite battery life. The chip can use any of these three methods of battery life improvement on its own or in any combination.
In early April 2018, the Materials Research Society held their spring meeting and exhibit at the Phoenix, Arizona convention center. With over 110 symposium presentations, it was difficult to select which sessions to attend. But one forum caught my eye, “AI for Materials Development”. These days AI seems to be everywhere.
As we all speculate about the impact of AI on autonomous driving and the next killer app, Carla Gomes, Professor of Computer Science and director of the Institute for Computational Sustainability at Cornell University, is focusing on large-scale constraint-based reasoning. She pointed out that AI still can’t compete with good ol’ human common sense. Human reasoning and inference planning are still lacking in most AI systems. One of the key fundamentals of AI is building a neural network that resembles the human brain. Even with the advancements of 7nm silicon technology, this is a daunting task, not to mention the complexities of software algorithms to mimic the human thought and decision process.
But in the world of materials development, AI excels. By integrating material experimentation and AI, the discovery of new materials and the application of materials in the real world is progressing at an accelerated pace. AI is capable of developing the hypotheses and—along with robotics—is following through with new scientific discovery.
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