The ups and downs are a pattern in Silicon Valley. In the downs, the layoff shakes people to the core. In the downs, many middle managers face both mid-life crisis and financial crisis at the same time. In the downs, the genZ realizes, a corporation is a corporation no matter the vision, the mission or the propaganda on the company web page. We are in the downs.
Ups and downs, Silicon Valley continues to be the center of many technology innovations. Some change the world, many do not; it’s just hard to differentiate between the two.
During the internet boom in the 90s, many folks resigned from big corporations and dreamed of their startup making it to IPO. They worked super long hours because of the hope that they would not need to work anymore after the IPO. It was those glory days that we asked each other whether we made it yet, and who has become millionaires overnight. Restaurants were full, highways were busy. Everyone was upbeat. It was like living in the Great Gatsy era. It has been a golden era.
Year 2K has been another buzz where the whole world was watching and maybe worrying how the 20th century transitioned to the 21 century. It is not so much of a Ponzi scheme. In hindsight, its crisis assessment has definitely been overblown. Yet it created so many IT job opportunities. The COBOL programmers, long considered as dinosaurs, came back alive and became hotly sought after. It was a mini-miracle there. Y2K came and went without much drama. It was a win-win.
After the Y2K, there was the Cloud Buzz. It was advertised as if Cloud would solve all the problems of all corporations. Every CIO put it as a priority and talked about getting on the wagon. It was so overblown for a few years, then went quiet. The same pitch deck can be used for so long before people ask for actual deliverables and results. After some more years of working out the kinks, it started to deliver. Cloud is just a thing that once you are on its platform, it is pretty hard to get out. This Cloud business would keep many busy for many future years.
Then came the voice assistant. No one seems to figure out how to make money with these hardware devices or voice assistants. The most popular use cases for these devices remain to be “set a timer”, “play me a song”, “tell me a joke”, “tell me the news”. It is ahead of its time and technology. It needs a few more years before natural language technology is ready.
Machine Learning has been quite a breakthrough, benefiting from the data explosion and the abundance of computing power. It would probably be another few more years to discover the full commercial value.
Generative AI is taking the world by storm.
Having AI to write news articles is not something new. A few websites have been using AI to write poems or write news, only that they were not professional and some had pretty poor quality overall. With the ChatGPT (Generative pre-trained transformer) or BARD, their trained language model provides the professional touch and is impressive so far. Chatting with these generative AIs, I can stop admiring how fast it learns and how much it improves each day, not unlike the first year of a baby.
Silicon Valley techies can test these generative AI with the real problems to solve. The generative AI, ChatGPT or BARD alike, has such a powerful language model that it summarizes better than some high-income professionals.
- Ask it “how to manage changes in a big corporation”, its advice is as good as, if not better, than someone in my company who has worked as a change advisor for years.
- Ask it to summarize lengthy articles, it gives a clean summary which is surprisingly logical and easy to follow.
- Ask it to explain “technical jargon”, it explains in English terms and helps you learn more than talking to a pro.
- Ask it to plan a trip itinerary, it gives a great start, and open to refine it along the way.
What impressed me the most is the language model, I feel that suddenly I have a “communication” person for anything I write to create more punchy and readable content. Disclaimer: I have not asked for the service of generative AI in this blog, and the blog continues to have the flaw of a human being.
Their limitations are quite obvious too. It is a language model. It cannot be extended, without a high price tag, to support images, urls, and other object types. It has no shame to make up urls or information as it sees fit. That quality of making things up is among the most humane parts of generative AI.
If you worry about generative AI can replace humans in many jobs. Worry not. It is going to take away some jobs, and will create more jobs. If you worry about generative AI means that you cannot stay relevant with the same skills, it may be time to keep learning new skills. I am ready to attend the Generative AI conference this weekend.
oliviatamccue 
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