How Tech Crashes: Hope Meets Reality Or at Least Negative Mood

There's a lot of hope in current technology valuations. Let's look at how hope worked in the 1990s.

Here's a chart of Amazon (AMZN). It gained roughly 6,000 percent from it's IPO to a peak in December 1999.

If anything the hype and hope around Amazon in 1999 was totally correct or even understated. Yet Amazon lost 95 percent of its value into its 2001 low.

Amazon has risen 200,000 percent from those lows.

I believe some of today's leading technology hopes and hypes are in a similar position as Amazon in the 1990s, except potentially worse off because they are trying to solve more difficult problems. The two technologies in question are advanced algorithms often called AI (such as automated driving) and gene editing.

Wired: WHEN IT COMES TO GORILLAS, GOOGLE PHOTOS REMAINS BLIND

IN 2015, A black software developer embarrassed Google by tweeting that the company’s Photos service had labeled photos of him with a black friend as “gorillas.” Google declared itself “appalled and genuinely sorry.” An engineer who became the public face of the clean-up operation said the label gorilla would no longer be applied to groups of images, and that Google was “working on longer-term fixes.”

More than two years later, one of those fixes is erasing gorillas, and some other primates, from the service’s lexicon. The awkward workaround illustrates the difficulties Google and other tech companies face in advancing image-recognition technology, which the companies hope to use in self-driving cars, personal assistants, and other products.

Google solved the problem by making the AI stupid: it no longer knows that gorillas exist. Problem solved. Except Google's photo algorithm is still broken. Here's what it returns for a search of "white couples"

Google's "AI" meets the dictionary definition of "retarded."

Some problems we think are hard may be easy for computers to solve very simple things humans do can be very difficult for machines, but if Google can't produce accurate photo identification after years of development, it suggests investors' timelines for self-driving cars may be far too optimistic—as Tesla's troubles have shown.

ZH: CRISPR Crashes After Study Highlights Potential Cancer Risk From Gene-Editing

Given the massive interest in this company and its gene-editing applications, Stat News asks an obvious question - if successfully CRISPR’d cells can seed cancers, why hasn’t this been seen before, and why haven’t the many CRISPR’d mice developed tumors?

Karolinska’s Haapaniemi said the effect shows up in large-scale experiments like hers and Novartis’ “but can be missed in small-scale studies where people only focus on editing one gene in one cell type.” In speaking to other scientists, she said, “it seems that other teams have noticed the effect of p53 on editing,” but have not highlighted it.

Along with difficulties that can emerge for these technologies, the other factor to layer on is social mood. At peaks in social mood, investors are hopeful. Wider society aside, there is clearly great optimism in the technology sector with the sector at all-time highs. Smaller and more speculative biotechs are also at all-time highs. Cryptocurrencies are popular. Even if the real outlook remains promising and progress is being made, investors will focus on negatives more as social mood turns. Old stories become new again as previously ignored weaknesses become a focal point. If there are real difficulties, it will add to a growing negative view.

The narrative will shift. In many cases negative narratives already exist, but they will become more powerful and more widely believed as social mood falls. The negative narratives may become the official narrative and stay that way, as happened with nuclear energy. Instead of GMOs saving the world, they cause cancer. Gene editing causing cancer. "Don't mess with Mother Nature." (Even the mobile phones cause cancer meme is coming back.) Cryptocurrencies are frauds, only criminals use them, they're a form of Ponzi scheme. Self-driving cars are death traps. If perfect self-driving cars are rolled out in 2025, but the public believes they are death traps, it could delay adoption for years or severely limit their use.

The change in mood and the narrative around technology is what will create a generational buying opportunity.