Organization: Edge AI may be the AI ​​direction with the largest current expected difference

Recently, many technology giants have accelerated their deployment of edge computing. On June 7, NVIDIA officially announced that it will display the NVIDIA Jetson edge computing platform suitable for autonomous machines and many other embedded applications at the 2023 Shanghai International Embedded Show from June 14 to 16, and bring ecological partners. Solutions built based on relevant software and hardware in multiple vertical industries such as transportation, industry, and robotics.

Working with Nvidia on edge computing is communications giant Qualcomm. Qualcomm recently announced its transition from a communications company to an edge computing company. As a leader in the global communications field, Qualcomm has expressed its urgency to rapidly carry out strategic transformation, which has aroused the market's renewed attention to edge computing.

Compared with cloud computing, which centrally deploys software and hardware resources in large data centers far away from users, edge computing places computing resources at the "edge" closer to users or devices, thereby achieving lower latency and higher efficiency. Good privacy and better cost.

As AI empowers thousands of industries, application scenarios continue to enrich, from text, picture, video generation, intelligent dialogue, virtual scenes, etc., the computing power provided by a simple large-scale computing center will not be able to meet the diverse AI operations Demand, computing power is moving towards generalization, and the edge side is one of the most important components in the AI ​​ecosystem. Edge computing has natural cost, latency and privacy advantages. It can also serve as an interface bridge to pre-process massive and complex requirements before passing them to large models. Therefore, edge computing power has become increasingly prominent as a blood vessel for AI to touch thousands of scenarios.

The latest research report from Minsheng Securities pointed out that the cloud large model can be regarded as a huge intelligent brain, with strong self-learning ability, and can absorb and learn all kinds of knowledge possessed by human beings. Large models are deployed at the edge to adapt to edge scenarios and computing power to carry the capabilities of the intelligent brain. In an increasingly competitive market, edge-side artificial intelligence will provide enterprises with safe and efficient solutions, thereby helping them maintain their leading position. Edge artificial intelligence is currently the most challenging artificial intelligence direction, because artificial intelligence has clearly moved from the cloud to the edge.

We have produced a special report "Edge Computing: A New Trend in AI Computing Power", which provides a detailed analysis of the investment logic of edge computing. It sorted out how edge computing can help the implementation of AI applications, which links in the industry chain are expected to benefit from it, and the list of core beneficiary companies. Friends in need are welcome to request it for free.

The above is the detailed content of Organization: Edge AI may be the AI ​​direction with the largest current expected difference. For more information, please follow other related articles on the PHP Chinese website!