At this year’s Google I/O, the electrifying atmosphere was palpable as Google unveiled its latest triumph in artificial intelligence—the Gemini project. This year’s keynote, delivered by Sundar Pichai amidst rousing applause, emphasized Google’s relentless drive to refine and enhance AI capabilities, pushing the boundaries of what technology can achieve in our daily lives.
The conference kicked off with a spirited recap of the year’s achievements and a peek into the “Gemini era,” a bold new phase in Google’s AI development. The introduction of Gemini, a model designed from the ground up to be natively multimodal, capable of processing and integrating text, images, video, and more, marks a significant leap forward. This model is not just an incremental update; it’s a transformational shift that promises to redefine how we interact with technology.
In a demonstration of its prowess, Google revealed that Gemini can handle complex, multimodal tasks with ease, showcasing examples from various Google ecosystems such as Search, Photos, and Android. For instance, the newly enhanced Google Photos now utilizes Gemini to allow users to interact with their photos in revolutionary ways—like asking the app to recall specific details from images without manually searching.
One of the most exciting announcements was the expansion of Gemini’s capabilities into consumer products. Now integrated across Google’s suite of applications, Gemini’s reach extends into everyday use, making advanced AI tools accessible to everyone. The introduction of Gemini Advanced and the announcement of its availability on mobile platforms underscore Google’s commitment to democratizing AI technology.
By Bob Brennan, VP, GM, Intel Foundry Services, Customer Solutions Engineering
Bob Brennan
Artificial intelligence isn’t just driving headlines and stock valuations. It’s also “pushing the boundaries of silicon technology, packaging technology, the construction of silicon, and the construction of racks and data centers,” says Intel’s Bob Brennan.
“There is an insatiable demand,” Brennan adds. Which is great timing since his job is to help satisfy that demand.
Brennan leads customer solutions engineering for Intel Foundry, which aims to make it as easy and fast as possible for the world’s fabless chipmakers to fabricate and assemble their chips through Intel factories.
“We are engaged from architecture to high-volume manufacturing—soup to nuts—and we present the customer with a complete solution,” Brennan asserts.
Inviting New Chipmakers in by Turning Intel Inside Out
That contrasts with a foundry like TSMC, which offers research and development, wafer fabrication and selected advanced packaging. Intel Foundry offers those services and a lot more—going beyond construction and helping with testing, firmware (the software that makes hardware work) and the intricacies of the global semiconductor supply chain.
What’s New: Today at Baidu* Create in Beijing, Intel Vice President Gadi Singer shared a series of collaborations with Baidu on artificial intelligence (AI), including powering Baidu’s Xeye* a new AI retail camera with Intel® Movidius™ vision processing units (VPUs); highlighting Baidu’s plans to offer workload acceleration as a service using Intel® FPGAs; and optimizing PaddlePaddle*, Baidu’s deep learning framework for Intel® Xeon® Scalable processors.
“From enabling in-device intelligence, to providing data center scale on Intel Xeon Scalable processors, to accelerating workloads with Intel FPGAs, to making it simpler for PaddlePaddle developers to code across platforms, Baidu is taking advantage of Intel’s products and expertise to bring its latest AI advancements to life.”
–Gadi Singer, vice president and architecture general manager, Artificial Intelligence Products Group, Intel
How the Camera Works: Baidu’s Xeye camera uses Intel® Movidius™ Myriad™ 2 VPUs to deliver low-power, high-performance visual intelligence for retailers. Thanks to Intel’s purpose-built VPU solutions coupled with Baidu’s advanced machine learning algorithms, the camera can analyze objects and gestures, while also detecting people to provide personalized shopping experiences in retail settings.
Gadi Singer, vice president and architecture general manager for the Artificial Intelligence Products Group at Intel, uses artificial intelligence to reshape scientific exploration. Before his role with AI, the 35-year Intel veteran helped create the first Pentium processor; led development of the first Xeon processors and the first Atom processor; and oversaw architecture for generations of the Intel Core processors. (Photo Credit: Walden Kirsch/Intel Corporation)
Intel vice president and architecture general manager for its Artificial Intelligence Products Group discussed his role at the intersection of science — computing’s most demanding customer — and AI, how scientists should approach AI and why it is the most dynamic and exciting opportunity he has faced.
Q. How is AI changing science?
Scientific exploration is going through a transition that, in the last 100 years, might only be compared to what happened in the ‘50s and ‘60s, moving to data and large data systems. In the ‘60s, the amount of data being gathered was so large that the frontrunners were not those with the finest instruments, but rather those able to analyze the data that was gathered in any scientific area, whether it was climate, seismology, biology, pharmaceuticals, the exploration of new medicine, and so on.
Today, the data has gone to levels far exceeding the abilities of people to ask particular queries or look for particular insights. The combination of this data deluge with modern computing and deep learning techniques is providing new and many times more disruptive capabilities.
“Customers including Accenture, a major aircraft manufacturing company and even Intel are already receiving tremendous value from Intel Saffron AI software. It digs into disparate data sources to surface customers’ best practices, providing them with the meaningful insights needed to resolve issues faster.”
– Gayle Sheppard, vice president and general manager of Saffron AI Group at Intel
What It Includes: The Intel Saffron AI Quality and Maintenance Decision Support Suite is comprised of two software applications:
Similarity Advisor finds the closest match to the issue under review, across both resolved and open cases, identifying paths to resolution from previous cases and surfacing duplicates to reduce backlogs.
Classification Advisor automatically classifies work issues into pre-set categories, regulator mandated or self-defined, speeding up and increasing reporting accuracy while improving operations planning.
One Use Case: Accenture*, a global professional services company, is already using Intel Saffron AI to help clients resolve issues faster and reduce wasted efforts in product testing and defect resolution.
What’s New: Today at Baidu* Create in Beijing, Intel Vice President Gadi Singer shared a series of collaborations with Baidu on artificial intelligence (AI), including powering Baidu’s Xeye* a new AI retail camera with Intel® Movidius™ vision processing units (VPUs); highlighting Baidu’s plans to offer workload acceleration as a service using Intel® FPGAs; and optimizing PaddlePaddle*, Baidu’s deep learning framework for Intel® Xeon® Scalable processors.
