If you are looking for an answer to the question What is Artificial Intelligence? and you only have a minute, then here's the definition the Association for the Advancement of Artificial Intelligence offers on its home page: "the scientific understanding of the mechanisms underlying thought and intelligent behavior and their embodiment in machines."
However, if you are fortunate enough to have more than a minute, then please get ready to embark upon an exciting journey exploring AI (but beware, it could last a lifetime) …
The firm expects the edge AI chipset market to reach $12.2 billion in revenues, outpacing the cloud AI chipset market, which will reach $11.9 billion in 2025. The transition, says the firm, will be propelled by the increasing focus on low latency, data privacy, and the availability of low-cost and ultra-power-efficient AI chipsets. Currently, the cloud is the center of AI, with most AI training and inference workloads happening in the public and private clouds. Traditionally, the centralization of these workloads in the cloud brings the benefits of flexibility and scalability. However, says the firm, the industry has witnessed a shift in the AI paradigm driven by the need for privacy, cybersecurity, and low latency.
The major Artificial Intelligence Chipsets producing areas include North America, Europe, Asia-Pacific, Middle-East, and Africa. Artificial Intelligence Chipsets industry states and outlook (2020-2027) is introduced in this part. Additionally, Artificial Intelligence Chipsets market dynamics stating the opportunities, market risk, and key driving forces are researched. Part 2: This part covers Artificial Intelligence Chipsets manufacturers profile based On their small business overview, product type, and program. Additionally, the sales volume, Artificial Intelligence Chipsets product cost, gross margin analysis, and Artificial Intelligence Chipsets market share of each participant is profiled in this report.
With respect to consumption, the report entails details about volume share and valuation, while deciphering the price trends over the forecast period. Information regarding import and export patterns across various geographies is provided in the report. Speaking of production, the study discusses the manufacturing of product, raw material procurement cost, and profit margins amassed by the key Deep Learning Chipsets market players, along with variations in unit cost offered by these manufacturers in several regions. More importantly, the report encompasses a detailed projection about the consumption and production patterns displayed by the Deep Learning Chipsets market in the upcoming years.
Data-driven experiences are rich, immersive and immediate. Think pizza delivery by drone, video cameras that can record traffic accidents at an intersection, freight trucks that can identify a potential system failure. These kinds of fast-acting activities need lots of data -- quickly. So they can't sustain latency as data travels to and from the cloud. That to-and-fro takes too long.
Data-driven experiences are rich, immersive and immediate. Think pizza delivery by drone, video cameras that can record traffic accidents at an intersection, freight trucks that can identify a potential system failure. These kinds of fast-acting activities need lots of data -- quickly. So they can't sustain latency as data travels to and from the cloud. That to-and-fro takes too long; instead, many of these data-intensive processes must remain localized and processed at the edge and on or near a hardware device.
The points that are discussed within the report are the major market players that are involved in the Deep Learning Chipset market such as manufacturers, raw material suppliers, equipment suppliers, end users, traders, distributors and etc.The growth factors of the market is discussed in detail wherein the different end users of the market are explained in detail.Data and information by manufacturer, by region, by type, by application is given and custom research can be added according to specific requirements. The Research projects that the Deep Learning Chipset market size will grow from in 2017 to by 2023, at an estimated CAGR of XX%. The base year considered for the study is 2017, and the market size is projected from 2018 to 2023.Akin to Artificial Intelligence (AI), the concept and possibilities of deep learning are being contemplated and harnessed for several decades. But, in the recent times, the technology pertaining to algorithmic chips has improved considerably, promising to revolutionize major applications such as data centers to the simplest of microcontrollers. "This report can be customized to meet the desired requirements. Please connect with our Team, who will ensure that you get a report that Fulfils your requirements."
The opportunity for AI accelerator chips is much-hyped, but how big is the market, and which companies are actually selling chips today? EETimes spoke to the reports' author, Principal Analyst Lian Jye Su, to gain some insight into which companies and technologies are making inroads into this potentially lucrative market. AI in the Cloud The first report, "Cloud AI Chipsets: Market Landscape and Vendor Positioning," highlights how cloud AI inference and training services are growing rapidly. The resulting AI chipset market is expected to grow from US$4.2 billion in 2019 to US$10 billion in 2024. Nvidia and Intel, the current leaders in this space, are being challenged by companies including Cambricon Technologies, Graphcore, Habana Labs and Qualcomm.