By Alexander Chiejina
Emerging technology such as Artificial Intelligence (AI) though not completely new in the tech space, has continued to receive positive reviews with experts predicting a continuous boom.
In line with the positive expert predictions, technology giants Microsoft and Google are going head-to-head in a battle believed to be the future of search (AI).
In November 2022, Microsoft unveiled its OpenAI’s ChatGPT chatbot to its Bing search engine. Another tech giant, Google in a swift move, introduced Bard (a rival to ChatGPT). In the wake of these developments, tech experts have placed both tech giants on a collision course as they contend to define the future direction of search.
Google and Microsoft are hugely invested in the AI space, and they have significant resources and expertise in AI research and development as they compete to establish dominance in this fast-growing field.
Google has been a leader in AI research for many years, with its research arm, Google AI, making significant contributions to the field. Google has also launched a number of successful AI products, such as Google Assistant, which is an AI-powered virtual assistant that performs a range of tasks for users.
Microsoft has only been making a strong push into the AI space in recent years and invested heavily in AI research and development. The tech giant has also launched a number of AI-powered products, such as Cortana, which is Microsoft’s virtual assistant.
In terms of market share, Google is currently the dominant player in the AI space. According to research firm IDC, Google had a 36.9 percent share of the AI market in 2020, compared to Microsoft’s 17.3 percent share. Microsoft, on the other hand, is making significant investments in AI, and the company has stated that it sees AI as a key area for future growth.
Microsoft has also made a number of high-profile acquisitions in the AI space. Microsoft’s incursion is through its OpenAI’s ChatGPT chatbot on its Bing search engine. Google’s rival ChatGPT is Bard.
Google’s Bard is powered by its TPU (Tensor Processing Unit) chips in its cloud service, said a source familiar with the company’s plans. Microsoft said its AI supercomputer in Azure – which likely runs on GPUs – can deliver results in the order of milliseconds, or at the speed of search latency.
It sets up a very public battle in AI computing between Google’s TPUs against the AI market leader, Nvidia, whose GPUs dominate the market.
Microsoft is using a more advanced version of OpenAI’s ChatGPT. Microsoft’s road to Bing with AI started with making sure it had the computing capacity with its AI supercomputer, which the company claims is among the five fastest supercomputers in the world.
The computing costs typically go up as more GPUs are implemented, with the cooling costs and other supporting infrastructure adding to bills. But companies typically tie revenue to the cost of computing.
Microsoft’s AI supercomputer was built in partnership with OpenAI, and it has 285,000 CPU cores and 10,000 GPUs. Nvidia in November signed a deal to put tens of thousands of its A100 and H100 GPUs into the Azure infrastructure.
Microsoft’s Bing search share does not come close to Google Search, which had a 93 percent market share in January, according to Statcounter.
Artificial intelligence is fundamentally a different style of computing predicated on the ability to reason and predict, while conventional computing revolves around logical calculations. AI is done on hardware that can carry out matrix multiplication, while conventional computing has revolved around CPUs, which excel at serial processing of data.
Google is taking a cautious approach and releasing its Bard conversational AI as a lightweight modern version of its LaMDA large-language model. Google’s LaMDA is a homegrown version that competes with OpenAI’s GPT-3, which underpins the ChatGPT conversational AI.
Google’s TPUs, introduced in 2016, have been a key component of the company’s AI strategy. The TPUs famously powered AlphaGo, the system that defeated Go champion Lee Sedol in 2016. The company’s LaMDA LLM was developed to run on TPUs. Google’s sister organisation, DeepMind, is also using TPUs for its AI research.
Facebook is now building datacenters with the capacity for more AI computing. The Facebook clusters will have thousands of accelerators, which include GPUs, and will operate in a power envelope of eight to 64 megawatts. The AI technologies are used to remove objectionable content, and the computing clusters will drive the company’s metaverse future. The company is also building an AI research supercomputer with 16,000 GPUs.
Cloud providers go through lengthy evaluation cycles of picking the best CPUs, GPUs and other components. The total cost of ownership is another consideration.
Datacenters that preferentially support AI workloads will see a little bit more uptake for both GPUs and CPUs from Intel, Nvidia and AMD. Some may choose alternate accelerators for AI workloads, but they could coexist with GPUs and CPUs.
Overall, the battle between Google and Microsoft for dominance in the AI space is likely to continue for the foreseeable future, as both companies continue to invest heavily in research and development in this area.