The ones of you who know me are very well aware that if there is something which has sort of obsessed me for the last few years, this is is definitely how to use analytics and AI to improve the venture industry.
While I tended to focus on scouting and evaluation, I learned that AI can be also used to spot general trends, identify market gaps, improve VCs portfolio management, better match co-investors and deals, gather intelligence on competitors’ landscape, identifying potential acquirers, and improve pricing models.
I have been thinking about those issues for a while now (and stay tuned because I will post over the next few months my latest research in this field), and did already write on the importance of using AI in VC, summarized some academic research on this topic, and generally wrote about AI investors and accelerators. Read More
Daily Archives: May 7, 2019
China’s state-run press agency has created an ‘AI anchor’ to read the news
Xinhua, China’s state-run press agency, has unveiled new “AI anchors” — digital composites created from footage of human hosts that read the news using synthesized voices.
It’s not clear exactly what technology has been used to create the anchors, but they’re in line with the most recent machine learning research. It seems that Xinhua has used footage of human anchors as a base layer, and then animated parts of the mouth and face to turn the speaker into a virtual puppet. By combining this with a synthesized voice, Xinhua can program the digital anchors to read the news, far quicker than using traditional CGI. (We’ve reached out to AI experts in the field to see what their analysis is.) Read More
Artificial Intelligence Is Creating A Fake World — What Does That Mean For Humans?
“Seeing is believing” or is it? There once was a time when we could have confidence that what we saw depicted in photos and videos was real. Even when Photoshopping images became popular, we still knew that the images started as originals. Now, with advances in artificial intelligence, the world is becoming more artificial, and you can’t be sure what you see or hear is real or a fabrication of artificial intelligence and machine learning. In many cases, this technology is used for good, but now that it exists, it can also be used to deceive. Read More
How Chinese Spies Got the N.S.A.’s Hacking Tools, and Used Them for Attacks
Chinese intelligence agents acquired National Security Agency hacking tools and repurposed them in 2016 to attack American allies and private companies in Europe and Asia, a leading cybersecurity firm has discovered. The episode is the latest evidence that the United States has lost control of key parts of its cybersecurity arsenal.
Based on the timing of the attacks and clues in the computer code, researchers with the firm Symantec believe the Chinese did not steal the code but captured it from an N.S.A. attack on their own computers — like a gunslinger who grabs an enemy’s rifle and starts blasting away. Read More
The Seven Deadly Sins Of AI Predictions
Mistaken extrapolations, limited imagination, and other common mistakes that distract us from thinking more productively about the future.
We are surrounded by hysteria about the future of artificial intelligence and robotics—hysteria about how powerful they will become, how quickly, and what they will do to jobs.
I recently saw a story in MarketWatch that said robots will take half of today’s jobs in 10 to 20 years. It even had a graphic to prove the numbers.
The claims are ludicrous. (I try to maintain professional language, but sometimes …) For instance, the story appears to say that we will go from one million grounds and maintenance workers in the U.S. to only 50,000 in 10 to 20 years, because robots will take over those jobs. How many robots are currently operational in those jobs? Zero. How many realistic demonstrations have there been of robots working in this arena? Zero. Similar stories apply to all the other categories where it is suggested that we will see the end of more than 90 percent of jobs that currently require physical presence at some particular site.
Mistaken predictions lead to fears of things that are not going to happen, whether it’s the wide-scale destruction of jobs, the Singularity, or the advent of AI that has values different from ours and might try to destroy us. We need to push back on these mistakes. But why are people making them? I see seven common reasons.
Overestimating and underestimating
Imagining magic
Performance versus competence
Suitcase words
Exponentials
Hollywood scenarios
Speed of deployment
Read More
Systems Archtypes
We live in the world of events. Things happen and we respond—a machine breaks down, we buy anew machine; sales drop, we launch an ad campaign; profits fall, we layoff workers. Each event creates another event, in an endless stream of cause-and-effect relationships. At this level of understanding,all we can do is react to things that are happening to us. If we begin to see the world as patterns of behavior over time, we can anticipate problems (patterns of machine breakdowns, cycles of sales slumps, periodic profit squeeze s) and accommodate them (schedule maintenance work, institutionalize ad cycles, sharpen cost-cutting skills ). Managing at this level allows us to anticipate trends and accommodate them. At this level, we are still responding to events, but in a more proactive manner. If we go deeper to the level of systemic structure, however,we can begin to see what creates the behaviors we observe, and then take actions to change the structures. This allows us to alter the source of a problem rather than just deal with the symptoms. The power of systems thinking comes from this focus on the level of systemic structure, where the greatest leverage lies for solving problems. Read More
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