There is no doubt that the number of applications for AI, ML, and automation is on the rise; this holds true across a wide range of industries, from consumer electronics to cybersecurity to semiconductors.
here is no doubt that by the year 2023, automation and artificial intelligence will have permeated every facet of human existence.
In Michael Dell‘s words, “building systems that are built for AI first is really inevitable.
Over the past decade, significant advancements have been made in artificial intelligence, greatly improving the technology’s ability to spot patterns and establish connections.
In the future, more and more creations will be guided by artificial intelligence. ChatGPT, developed by the artificial intelligence (AI) research and deployment company OpenAI, is a good current example.
The accuracy and precision of this program’s results have recently made headlines. Teachers are modifying lesson plans, for instance, to discourage students from relying solely on ChatGPT to complete students’ essay assignments.
There is concern because hackers are known to be using ChatGPT to develop malicious software, and security researchers have uncovered this.
That’s a common indicator of an app’s widespread adoption. The question is, how good can it really be? Can AI generate meaningful foresight into the future of AI and automation?
How AI and Automation is impactful?
Because of the improvements in computing technology, artificial intelligence (AI) and automation are playing a larger and larger role in modern society.
Over the course of the last few decades, computing has shifted from relying on large, monolithic CPUs for general-purpose tasks to instead relying on multiple CPUs, GPUs, and now, specialized AI and ML accelerators for more efficient performance.
Software has evolved alongside the emergence of new forms of computing to take advantage of their superior features.
Containerized, scale-out applications built on platforms like Docker and Kubernetes have replaced traditional, large, monolithic scale-up programs.
The development of high-speed, high-bandwidth Ethernet networking based on leaf-spine architectures has allowed for this shift in the computing industry.
Broadcom is a pioneer in the market for high-speed Ethernet switches. They have made it possible for networks to meet the challenges of AI and ML applications.
To give just one example, their 51.2Tbps Tomahawk 5 switch chip has features that dramatically accelerate AI and ML workloads, and it offers twice the bandwidth of any other networking silicon.
ChatGPT’s capabilities rely on highly scalable networks that link tens of thousands of accelerators.
This paves the way for AI and ML to be executed on a massive scale, opening the door to novel and potent applications in fields like autonomous vehicles, NLP, and IR.
To sum up, developments in computing, such as the emergence of dedicated AI and ML accelerators, and the use of containerized, scale-out applications are allowing AI and automation to play a larger role in today’s world.
High-speed, high-bandwidth Ethernet networks connecting various forms of compute elements have made these developments possible.
Broadcom will play a pivotal role in driving future exciting technological developments as technology continues to advance.
ChatGPT did a great job of summarizing where we stand on AI and robotics. We recognize that our efforts to date have barely scratched the surface, an agree that the phrase “at scale” deserves special emphasis.
The real benefits of AI and automation won’t be realized until they can be applied frequently and on large scales, as is made possible by modern Ethernet networking technologies.
To read our blog on “Sanctuary AI has deployed “World’s 1st human-like robot,” click here.
