A. Ham

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On November 13, 2018, A. Ham commented on Realizing the Promise of Additive Manufacturing at Boeing :

In relation to the materials challenge, Lockheed Martin is working on utilizing AI to ensure quality of the internal structures of its additively manufactured parts: https://news.lockheedmartin.com/2018-10-01-Lockheed-Martin-Contract-to-Marry-Machine-Learning-with-3-D-Printing-for-More-Reliable-Parts. As companies in defense and aerospace move forward on parts which have an extremely rigorous quality control process, utilizing all available technology becomes even more important. By utilizing AI and requiring less operator input, you can fix some of the talent issues on the machine operations front in the short term. In the long term, I see competition for AM design talent as a major driver of company success against Boeing’s rivals in aerospace.

On November 13, 2018, A. Ham commented on Empire State of Minds: Open Innovation in NYC :

Civic duty is not enough, but it can be a start. Offering grants, prizes, or a job to the winners of innovation contests would certainly be cheaper than 2.5 billion dollars per mile. In addition, the city could leverage the civic arms of its highly profitable businesses. There are some people working in NYC who are highly trained in evaluating start up ideas and valuing companies. If the government brought some of them in as advisers or judges, they could improve the success rate of the projects and contests. They could even utilize some of them as an independent arm with different rules about distribution of funds in order to eliminate red tape, a strategy the Department of Defense is piloting now with Defense Innovation Unit.

On November 13, 2018, A. Ham commented on A 3D-printed liver: not ready for prime time? :

I believe the ExVive still provides value addition to companies that must still undergo human trials. The closer a company can get to replicating the environment inside of a living being, the more information it can gather about its product. By providing a better platform for testing, Organovo could potentially save companies millions of dollars in R&D costs by ruling out bad solutions more accurately than previous testing. By eliminating some options higher in the funnel, the drug companies would be able to raise their efficiency and success with long-term, in vitro trials, raising their profits.

Do you think ES&S provides a good model for companies that fulfill government contracts for national critical infrastructure?

I don’t think they are doing enough to fix vulnerabilities within their existing equipment. The information about their products’ flaws is already on the market. By ignoring opportunities to upgrade based on exploits that already exist, they are doing a disservice to the American public. For future technologies, I think their hybrid approach to innovation would be appropriate.

On November 13, 2018, A. Ham commented on Craft beer by the people, for the people :

I see a way forward that combines your customer retention recommendation with the brewery’s desire for better data collection: a pub of their own. By creating an experimental brewpub that offers a few constantly improving staples and a few highly variable wildcards, they can create an environment that encourages people to try and react to their beer much more quickly than their current process. Having a large variety of delicious but “safe” beers available will help with retention. To drive innovation, they could offer smaller pours of the wildcard beers and immediately give discounts for those who participated in the iterative learning process by reviewing their beers. This could speed the iteration time by getting more data faster. I think that AI-enabled beer glasses are a bit excessive, but if they can make it work, it would give them a data-collection advantage over their rivals.

On November 13, 2018, JWG commented on Ford: Using Machine Learning To Humanize Vehicles :

As someone who has driven a vehicle in some pretty stressful situations, I’d argue that when you’re displaying “danger” is the best time for a machine to take over. As levels of stress go up, human performance declines significantly. By taking over when you are at your worst, the AI driving the car is more likely to prevent an accident by driving by itself.

The potential to establish a link between autonomous cars could fix the issue of emergencies. If autonomous vehicles were able to communicate, they could move out of the way for a vehicle experiencing an emergency, allowing you to get to the hospital faster. This would also have a use case for mechanical failure. I recently had a break line blow out but had no way to effectively communicate that with other cars in the area as I barreled through a stop sign at 30 MPH. An autonomous vehicle would have been able to send out a danger signal to others in the area and keep them clear, preventing an accident.

I think the partnership will be successful and their position defensible for one reason: the data set. Rolls Royce is also partnering with Maersk, the industry leader in shipping, which will allow them to continue to develop their models with additional data added from Maersk ships. Through this additional data, they will have better inputs and therefore better operational outcomes. As you say, there will be large CAPEX necessary to launch similar projects, making it prohibitively expensive for another company to achieve a similar level of quality and gain the industry’s trust.