In this Chip Chat podcast, Diane Bryant, EVP/GM for the Data Center Group at Intel, discusses how the company is driving the future of artificial intelligence by delivering breakthrough performance from best-in-class silicon, democratizing access to technology, and fostering beneficial uses of AI. Bryant also outlines her vision for AI’s ability to fundamentally transform the way businesses operate and people engage with the world.
At an AI event in November, Intel CEO Brian Krzanich shared how both the promise and complexities of AI require an extensive set of leading technologies to choose from and an ecosystem that can scale beyond early adopters. As algorithms become complex and required data sets grow, Krzanich said Intel has the assets and know-how required to drive this computing transformation.
In a blog Krzanich said: “Intel is uniquely capable of enabling and accelerating the promise of AI. Intel is committed to AI and is making major investments in technology and developer resources to advance AI for business and society.”
At the event, Bryant also announced that Intel expects the next generation of Intel Xeon Phi processors (code-named “Knights Mill”) will deliver up to 4x better performance1 than the previous generation for deep learning and will be available in 2017. In addition, Intel announced it is shipping a preliminary version of the next generation of Intel Xeon processors (code-named “Skylake”) to select cloud service providers. With AVX-512, an integrated acceleration advancement, these Intel Xeon processors will significantly boost the performance of inference for machine learning workloads. Additional capabilities and configurations will be available when the platform family launches in mid-2017 to meet the full breadth of customer segments and requirements.
AI was also front and center at the Intel HPC Developer Conference at SC16 in Salt Lake City. In this video from the Intel HPC Developer Conference, Ananth Sankaranarayanan from Intel describes how the company is optimizing Machine Learning frameworks for Intel platforms. Open source frameworks often are not optimized for a particular chip, but bringing Intel’s developer tools to bear can result in significant speedups.
You can see a full set of interviews and presentations from with industry thought leaders in our Intel AI Video Gallery.