Dear Friends and Students,
According to an Accenture report, "40% of working hours across industries can be impacted by Large Language Models (LLMs)" (Accenture.com).
In the early 90s, I used a typewriter and prepared for a typewriting test called "Lower." My friends suggested that learning Typewriter was a prerequisite for Computers! Now looks funny right!! We used to stand in long queues and book slots to learn. When I share these memories with my children, they are amused because today each has their own personal laptop, tablet, and mobile device. If you had certificates in Typing (Higher and Lower) and Stenography, your job was almost guaranteed. This was the scenario in the 90s. Today, typewriting and stenographer jobs have become extinct.
GPT-4 (OpenAI's large multimodal language model that generates text from textual and visual input) can generate automated responses to customer queries, which eases the workload of customer support teams. It can even code a website from an image of an outline and achieve a high degree of accuracy in academic tests.
However, it doesn't stop there. It is gradually making its way into the engineering world. For instance, IBM Smart Edge for Welding on AWS can analyze the quality of welds. Visual inspection is tedious, highly error-prone, and often misses welding defects, but computer vision systems can detect anomalies and welding errors with a high degree of accuracy. This is just the beginning.
A day is not far when your laptop will be connected to a household 3-D printer, and you can make a request (Prompt, that is the future of Prompt Engineering) to "change the color of your sandals to match a party outfit for the rainy season." This prompt/request will be sent to a cloud-based LEM (Large Engineering Model, e.g., AWS server), which will modify the old sandals by changing their texture and color and then print the new ones. This LEM will know material science, weather data, locational data, personal preferences of various parties, ergonomics (covering anatomical arch support, shock absorption, resistance to mold, fungus, bacteria, and odor), and more.
Similar LEMs will be connected to other LEMs in electrical and heavy engineering, and possibly in every engineering, medical, or industrial process, accessible as API calls. That is the future of LEMs!
CNBC reports that Google and the Department of Defense are building an AI-powered microscope to help doctors spot cancer. On a positive note, expert oncologists are supported by AI, but on the negative side, mediocre oncology jobs may be replaced by AI.
AI is like an elephant! You can become a Mahout and tame the elephant, or you can play with a mad elephant and get crushed. Decide and prepare accordingly!
Ravi Saripalle
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