Kick Off
There’s been a lot of handwringing about the algorithms driving what we see related to political news. First, a month ago, there was concern that Facebook’s news feed results were biased against conservative news, and this week, there’s concern that Google favors Hillary Clinton in its autocomplete suggestions in its search engine. (See this YouTube video that went viral on that. The video shows that Google seems to have suppressed the appearance of “Hillary Clinton indictment” in favor of “Hillary Clinton India,” even though data shows people search for information on Clinton’s indictment more than information on Clinton and India. It points out that the executive chairman of Google’s parent company, Eric Schmidt, is a big Clinton supporter and that Google has many ties to her as well.)
Search engines and algorithms decide what’s relevant on these sites in very complicated ways, and the public generally doesn’t know when it gets tweaked. Generally speaking, people want artificial intelligence. It’s making life much easier in many ways. But who is to say that AI isn’t going to conclude that one candidate is just better. Any given AI may simply conclude that Trump or Clinton or Sanders, for that matter, is unfit to be president. We live in a world where the media tries to cover candidates equally (may not seem that way with some outlets, but generally there is an effort at media companies to give equal coverage). An AI model wouldn’t generally be programmed to bend over backwards to treat candidates evenly. Though, apparently, Google’s search engine is programmed to never autocomplete to something related to a crime, which some say is why “indictment” doesn’t come up with Hillary Clinton.
My view on all this is that these news feeds and searches are a type of public utility and that it is unacceptable for corporate agendas to tinker with the results we see to further their own interests. That said, I do not think Google and Facebook need to go into the algorithms and change them in ways to make them seem unbiased. If the behavior of the public in search queries drives these algorithms to give biased results, so be it. But it’s got to be based on the public, not on corporate interests.
In the News
Google announced that it had made progress in quantum computing. Interestingly, it’s a different technique, called “analog quantum computing” that tries to borrow less from regular digital computing in its pursuit of the new technology. To me, it’s also a tacit acknowledgement that “D-Wave”, the quantum computing company that Google invested in, has failed to live up to the hype. This article says as much in passing.
Microsoft released a research paper showing that it has figured out how to predict whether people will have pancreatic cancer based on their search queries. This reminds me a bit of when Google studied search data to predict flu outbreaks. But the difference here is the Microsoft research gets at something far more personal. It also raises an interesting ethical question: what should Microsoft do if it’s models predict someone has cancer? Is Microsoft obligated to tell them? Good summary here.
It’s somewhat amusing watching the lions of technology stoop to personal insults to support their views about artificial intelligence. As you all have likely read, Elon Musk is concerned that AI may ruin the world. On the other side of the debate, Eric Schmidt says that’s not going to happen. So this week, what did Schmidt say to get a leg up on their dispute? That Musk is not a “computer scientist” and is only an “engineer,” so he doesn’t know what he’s talking about.
In Industry
In our open-source corner of the world, Doug Cutting, the creator of Hadoop, gave an interview this week where he talks about the performance improvements we can expect to see from “XPoint,” a new memory chip being produced by Intel that will allow much faster access to much larger datasets. Cutting talks about how Cloudera and Hadoop will benefit from this new hardware. But these new chips are part of a steady trend towards big-data computing where data resides “in memory,” where it is faster to access than when it’s on disk. Personally, I can’t wait to run the open-source data platform I work on (Pyfora) on top of this hardware!
Chip wars: NVIDIA has been getting a lot of positive attention for its chips, and I’ve written in the past about the shift from CPUs to GPUs (a big marker in that story was earlier this year when a computer beat a world champion at Go). Something to watch for now are hybrid chips that combine features of the two kinds of computing devices, such as the Intel Xeon Phi. Here’s a thoughtful essay on the trade-offs in all these kinds of chips and where the industry is heading.
In cancer research, data analysis is coming up a lot. This week, UCLA researchers announced a method for using genetic sequences to more accurate tell cancer patients how their cancer is likely to turn out. And Vice president Biden spoke at a national oncology conference about the need for data sharing to crack the code on curing cancer.
Quirky Corner
There’s a new movie out, completely written by artificial intelligence. And, coming soon, is AI songwriting.
Tesla now knows whether an accident is your fault. I bet it’s not long before all cars do. This will be potentially a big change in how the police and insurance companies handle blame in car collisions. So, that 1990’s rust-bucket you have parked in your driveway may break down occasionally, but at least it won’t tattle on you.
What’s happening at Ufora
I was interviewed on the Talk Python podcast about our work on auto-scaling python programs to thousands of cores using Pyfora. The show’s host, Michael Kennedy, asked me some great questions about the technology inside of Pyfora, and some of the work we’re doing now to speed up complex learning algorithms.
Also, we’re excited that as of this week, the fine folks at MLconf will be sharing this newsletter with their audience. Welcome MLconf fans!
Braxton McKee is the technical lead and founder of Ufora, a software company that has built an adaptively distributed, implicitly parallel runtime. Before founding Ufora with backing from Two Sigma Ventures and others, Braxton led the ten-person MBS/ABS Credit Modeling team at Ellington Management Group, a multi-billion dollar mortgage hedge fund. He holds a BS (Mathematics), MS (Mathematics), and M.B.A. from Yale University.