Construction and AI, a bitter lesson that many will learn

One of the nice things about changing this blog to discuss construction over data centers is the audience is much broader. An example is the application of Artificial Intelligence (AI) to construction. If you Google “construction AI” you will have a wide range of companies and articles on the topic. If you talk to any big company in the construction ecosystem you will get a confirmation that they are working on the use of AI in construction. So all is good. Construction will soon have AI systems making construction better. Having worked on the construction problem for over 10 years I am more skeptical of what will be done. Why? One example is the very nature of how AI systems get developed. 

One of my super smart old friends shared this YouTube video.  How smart is he? He worked at Apple, Adobe, Microsoft, Google, Facebook, and startups. How old a friend? Have known him for 30 years.

The above video refers to this paper.

I find it interesting that so many times well written papers have the most interesting part at the end, but so many readers don’t make it to the end. Or by the time they get to the end they aren’t looking for the big points. At the end of this paper is the observation that the fundamental approach to AI is flawed. 

 “The second general point to be learned from the bitter lesson is that the actual contents of minds are tremendously, irredeemably complex; we should stop trying to find simple ways to think about the contents of minds”

This observation is based on studying 70 years of AI efforts and figuring out what works and what doe not. The YouTube video provides some nice graphics to illustrate this point with examples.

Now the biggest problem with doing this as this paper suggests is it says do not build your AI system with knowledge from your expert users. It feels good and is satisfying in the short term. Huh. What other things in life are bad for you that feel good and provide short term satisfaction, but plateaus and inhibits further progress. 

So what do you do? Take a contrarian approach. One based on search and learning that scales with computational capabilites. Huh what businesses have made a success based on search and learning? Google. Facebook. Amazon retail. They are all disrupting businesses with AI.

”breakthrough progress eventually arrives by an opposing approach based on scaling computation by search and learning. The eventual success is tinged with bitterness, and often incompletely digested, because it is success over a favored, human-centric approach.” 

Well off to Google Cloud Next 19 in SF. Ready to see what they are selling to win the battle against AWS and Azure.

Heading to Google Cloud Next '19, Apr 9-10

Google’s Cloud event is on Apr 9-11 in SF at Moscone Center. Cloud infrastructure is the industry standard. 5G architects realized in order to scale support micro services they need a cloud native design. AWS is famous for the Cloud. But in many ways Google started with Cloud ideas before AWS. The challenge is Google is more of a technical company than a Amazon and they don’t talk about the Cloud in the way as AWS.

This is my first Google Cloud event. I have track and watched from afar, and thanks to some friends I am attending Google Cloud for the first time. I don’t plan on live blogging.

One of my friends though wanted me to share my impression of Google’s communication strategy and how well that works. That is complicated to articulate, and I’ll give it a shot though to share some observations.

Here are some of the tracks.

AWS emerged organically to be a Trillion Dollar baby, not invented by any one person

Medium has a 4 year old post from Jan 2015 interviewing Andy Jassy. The paragraph that caught my eye is Andy describing the beginning. The invention of AWS.

Amazon Web Services wasn’t any one person’s single idea. No proverbial apple fell on some Newton’s head, no Henry Ford or Steve Jobs-like character had a brainstorm. Instead, it rather emerged. The idea grew organically out of the company’s frustration with its ability to launch new projects and support customers.

The other part was the willingness to experiment and fail.

Invention”, says Jassy, “requires two things: 1. The ability to try a lot of experiments, and 2. not having to live with the collateral damage of failed experiments.

These are good lessons to think about when creating new services.

How smart should the edge be? Think of it as too many cooks in the kitchen

Quantamagazine has an article on smart things.

Smarter Parts Make Collective Systems Too Stubborn

As researchers delve deeper into the behavior of decentralized collective systems, they’re beginning to question some of their initial assumptions.

The article is makes good points using a goldilocks analogy of not too hot, not too cold to get a balance. I like to think of it as too many cooks in the kitchens. If you have too many intelligent things like too many cooks in the kitchen there are mental battles over who gets to make the decisions.

If you are at at the edge and have all the data should you let the central authority over rule your decision? How do you send commands from the central authority to say the way you are making your decisions is wrong. How do you know? I am at the edge and everything is running fine. Central authority, I can see how your edge performance compares to others and it is below the average of others. Change your decisions. OK, change what? I don’t know I am not at the edge you are. Uh, I am doing the same thing all the rest of the edge nodes are doing. Maybe there is a condition at my edge environment that is causing my poorer performance. There are dozens of services running at the edge. Well hundreds, maybe thousands. What do you suggest i change?

It’s like a second wave of this kind of research,” Kao said. “The first wave was naive enthusiasm for these collective systems. Now, it feels like … we’re questioning a lot of the assumptions we made initially and finding more complex behaviors.

Did Theranos’s Elizabeth Holmes avoid contact with Bill Gates? Her anti-BillG power was David Boies

Bill writes a review of John Carreyou’s Bad Blood book

 “Theranos is the worst-case scenario of what happens when a CEO prioritizes personal legacy above all else—but I hope that people don’t use it as an excuse to write off the next young woman with a big idea. I also don’t want Bad Blood to scare people away from next-gen diagnostics. Theranos went to extraordinary lengths to get around quality standards. The industry is highly regulated, and new diagnostics undergo rigorous testing.”

What got me curious is thinking about what would happen if Elizabeth Holmes was in a Steve Jobs or Bill Gates review. It is hard to imagine we should survive and they both would say the idea is good, but this is the wrong person to get it done. Steve passed away in Oct 2011 so he has no overlap with Elizabeth. Bill is still going and he is passionate about human health. It is ironic that Steve Jobs and Bill Gates as inventors is often referenced by 

Elizabeth had nothing to fear from running into Steve Jobs. Her biggest fear could be Bill Gates getting a peak at what Theranos was inside. I think Elizabeth was careful to stay clear of Bill Gates and his inner circle of health advisors. The vent diagram had no overlap. Well there is one overlap between Theranos and Bill Gates. That was David Boies.

  • At Cravath, he represented the Justice Department in the United States v. Microsoft Corp. case. Boies won a "victory" at trial,[10] and the verdict was upheld on appeal. The appellate court overturned the relief ordered (breakup of the company) back to the trial court for further proceedings. Thereafter, the George W. Bush administration settled the case. Bill Gates said Boies was "out to destroy Microsoft".[11] In 2001, the Washington Monthly called Boies "a brilliant trial lawyer", "a latter-day Clarence Darrow", and "a mad genius" for his work on the Microsoft case.[10]

With David Boies on the Theranos board and representing Theranos as an attorney there is no way Bill would get close to Theranos. So did Elizabeth Holmes add David Boies to protect her from Bill Gates?She did hire David Boies to protect the company and go after the whistleblowers. That didn’t quite work as the biggest heroes from the Theranos saga are the whistleblowers - Elizabeth Cheng and Tyler Schultz. Below are both of them speaking at a Stanford University event.