Recently, Google announced new Cloud TPU Virtual Machines (VMs), which provide direct access to TPU host machines. With these VMs, the company offers a new and improved user experience to develop and deploy TensorFlow, PyTorch, and JAX on Cloud TPUs. Customers could already set up virtual instances in Google Cloud with the TPU chipsets. However, this presented some drawbacks as the instances did not run in the same server environment. The TPUs were connected to the chipsets remotely via a network connection, reducing the processing speed since applications had to send the data over the network to a TPU and then wait for the processed data to be sent back.

The Hot Chips 31 Symposium started this week. AI (artificial intelligence) was the hot topic among participants Intel (INTC), NVIDIA (NVDA), and Advanced Micro Devices (AMD). The stocks of these three chip companies rose 1.18%, 2%, and 3.2%, respectively, on August 21 as they discussed their AI strategies. It is essential for long-term investors to understand the three companies' AI opportunity. All three have a different approach to tapping AI, so their AI TAM (total addressable value) is also different.

A much discussed area in technology these days is artificial intelligence, a type of machine learning. Artificial intelligence is a workload that requires an immense amount of processing power, which is why companies like microprocessor giant Intel (NASDAQ:INTC) -- a company that brings in tens of billions of dollars from sales of processors -- see this market as an interesting long-term growth opportunity. Interestingly, although Intel is a major supplier of processors for artificial intelligence workloads, the company doesn't get nearly as much attention for its efforts in this market as does graphics specialist NVIDIA (NASDAQ:NVDA) -- a company that has seen significant revenue and profit growth from artificial intelligence applications as its long-term investments in this space are paying off. Intel went over its artificial intelligence strategy at its Feb. 9 investor meeting. Let's look at what the company had to say about the market and how it plans to win in it.

Intel and data management company Cloudera have jointly launched a solution aimed at speeding up the process of machine learning (ML) and artificial intelligence (AI) workloads. The need for next generation predictive analytics, with insights being used on real-time automated decision processes has become more relevant to the business layer as enterprises dependence on data increases. The newly launched solution, Benchmark, has been tested on Cloudera with Apache Spark and the Intel Math Kernel Library (Intel MKL) to address their need for speed. The companies claim that by combining Spark, Intel MKL libraries, and Intel's optimised CPU architecture machine learning workloads can scale quickly. As machine learning solutions get access to more data they can provide better accuracy in delivering predictive maintenance, recommendation engines, proactive healthcare and monitoring, and risk and fraud detection.