Is Silicon Valley dead?
The outbreak of COVID-19 may have been the straw that broke the camel’s back in the struggling survival of Silicon Valley in California. A mix between the lock down, the cost of estate and the decline of technical staff willing to remain in California are but a few of the driving factors behind the death of an era and a city built around it. We began seeing a mass exodus of very large technology firms from California. A majority of them were opening new offices in Texas and a few were migrating to nearly 100% work from home positions.
By Scott Hamilton
Senior Expert Emerging Technologies
The outbreak of COVID-19 may have been the straw that broke the camel’s back in the struggling survival of Silicon Valley in California. A mix between the lock down, the cost of estate and the decline of technical staff willing to remain in California are but a few of the driving factors behind the death of an era and a city built around it. We began seeing a mass exodus of very large technology firms from California. A majority of them were opening new offices in Texas and a few were migrating to nearly 100% work from home positions.
Among those leaving California were Elon Musk, high profile technology entrepreneur, Peter Thiel and Keith Rabois, venture capitalists investing in the tech industry and big companies like Oracle and HP Enterprise. They were losing tech workers with the ability to work remote as they discovered the joys of living in less crowded and less expensive communities. This of course was just one factor playing in to the changes in Silicon Valley.
Alan Kay, Smalltalk inventor said in 1971, “Don’t worry about what anybody else is going to do… The best way to predict the future is to invent it. Really smart people with reasonable funding can do just about anything that doesn’t violate too many of Newton’s Laws!” Smalltalk was the programming language of the day that laid the foundations for MacIntosh, Microsoft Windows, the Linux X-Windows system and many other graphic user interfaces still in use today.
Kay’s words rang true in 2020, though in a way that no one expected. The COVID-19 virus was created in a lab, interesting enough just before the end of President Trump’s time in office. Anthony S. Fauci, M.D., NAID Director, shockingly warned President Trump that there would be a global pandemic during his presidency, and we needed to be prepared. How did he know, or at least suspect the virus? I’ll let you consider the opinions on that one.
If investors, inventors, business developers and governments come together to solve the hard problems society faces today we can together create a bright future. However, one thing remains certain, the inventions we most desperately need take us in a very different direction than big tech, big pharma and big oil are leading today. The massively divided landscape of the industries and their past failures to work together leave us with lacking skills that cross scientific disciplines. For example, in 2020 alone there were 21,000 biomedical research papers making reference to artificial intelligence and machine learning among which were the mRNA vaccine development methodologies used to create the Moderna vaccine in only two days after Yong-Zhen Zhang, Chinese scientist, released the genetic sequence of the virus!
The latest prediction is that the next Silicon Valley will be the merger of machine learning, biology and materials science. This marks the end of Silicon Valley as we know it because the skills required are completely different. Machine learning, statistical analysis and programming will still be needed, but it must be combined with a deep knowledge of the relevant science.
The opportunities of machine learning in research and development among the scientific community is profound, but leads to challenges in the way we approach the science. In the past we have relied solely on theory and experimentation. Arthur C. Clarke wrote, “Any sufficiently advanced technology is indistinguishable from magic,” could he have been predicting a future where our own science would leave our understanding behind? Machine learning is able to compare and contrast massive amounts of data and see correlations and predictions that human theories will struggle to explain. Without better understanding of our technologies, we may allow them to send us down paths that takes us to the edge of cliff.
I would argue that we have reached a cliff edge with social media as it becomes profoundly more difficult to distinguish the truth (facts), from the lies (opinions) expressed so openly on the platforms. Allowing the platforms, like Facebook and Twitter to make the decision through open censorship based on their version of the story is just as dangerous as leaving everything open and free. If you do a search today for the safety of the COVID-19 vaccines you will find factual information on both sides of the issue, with big tech filtering content based on their opinions, with little or no medical training to steer society in one direction, off the edge of the cliff.
Until next week stay safe and learn something new.
