IBM Thinks It Can Crack Pharmaceutical Code with AI
December 20, 2017
Artificial intelligence has been tasked with solving every problem from famine to climate change to helping you pick a new favorite song. So, it should come as no surprise that IBM thinks it can revolutionize another industry with AI. We learned exactly what from a Digital Trends story, “IBM’s New AI Predicts Chemical Reactions, Could Revolutionize Drug Development.”
According to the story,
As described in a new research paper, the A.I. chemist is able to predict chemical reactions in a way that could be incredibly important for fields like drug discovery. To do this, it uses a highly detailed data set of knowledge on 395,496 different reactions taken from thousands of research papers published over the years.
Teo Laino, one of the researchers on the project from IBM Research in Zurich, told Digital Trends that it is a great example of how A.I. can draw upon large quantities of knowledge that would be astonishingly difficult for a human to master — particularly when it needs to be updated all the time.
It’s an absolutely valid plan, but we aren’t sure if IBM is the one to really pull off this trick. IBM trying to work in big pharma seems kind of like your uncle tinkering on his “inventions” out in the shed. We’d rather see someone whose primary focus is AI and medicine, like Certara, PhinC, and Chem Abstracts.
Patrick Roland, December 20, 2017
Dark Cyber, December 19, 2017, Now Available
December 19, 2017
Dark Cyber (a new series from Stephen E Arnold, publisher of Beyond Search) provides an insider’s look at Oxygen Forensic Detective. The December 19, 2017, video explains what information can be extracted from a mobile computing device by investigators. The Detective software includes a function which can identify, extract, and organize contacts from the mobile device and from cloud services to which the device owner connected. The investigator can then click to see the most frequently called contacts and display the location of individuals on a digital map.
Stephen E Arnold said:
Individuals who engage in high-risk behaviors lack a good understanding of the information which can be pulled from a mobile computing device. Oxygen Forensic Detective is one example of the remarkable investigative and analytic tools now in active use in more than 100 countries by enforcement and intelligence personnel.
He added:
Detective is able to extract high-value information from messaging applications as well as more than 5,000 separate programs which run on a mobile computing device. Oxygen Forensics’ technical team releases frequent updates which allows Detective users to keep pace with rapid technical changes in the mobile computing sector.
The December 19, 2017, Dark Cyber program also reveals that Wikipedia has a Dark Web presence. The Dark Cyber research team notes that when high-value sites make their content available on the Dark Web, that content acts like a magnet to pull new users to the obfuscated Tor environment.
The program concludes with news that 18 Bitcoin ATM machines will be online and available in Atlanta, Georgia. A Bitcoin ATM makes it easier to convert digital Bitcoin into hard cash in the form of US dollars.
You can view this week’s video at this link.
Plan for 100,000 Examples When Training an AI
December 19, 2017
Just what is the magic number when it comes to the amount of data needed to train an AI? See VentureBeat’s article, “Google Brain Chief: Deep Learning Takes at Least 100,000 Examples” for an answer. Reporter Blair Hanley Frank cites Jeff Dean, a Google senior fellow, who spoke at this year’s VB Summit. Dean figures that supplying 100,000 examples gives deep learning systems enough examples of most types of data. Frank writes:
Dean knows a thing or two about deep learning — he’s head of the Google Brain team, a group of researchers focused on a wide-ranging set of problems in computer science and artificial intelligence. He’s been working with neural networks since the 1990s, when he wrote his undergraduate thesis on artificial neural networks. In his view, machine learning techniques have an opportunity to impact virtually every industry, though the rate at which that happens will depend on the specific industry. There are still plenty of hurdles that humans need to tackle before they can take the data they have and turn it into machine intelligence. In order to be useful for machine learning, data needs to be processed, which can take time and require (at least at first) significant human intervention. ‘There’s a lot of work in machine learning systems that is not actually machine learning,’ Dean said.
Perhaps poetically, Google is using machine learning to explore how best to perform this non-machine-learning work. The article points to a couple of encouraging projects, including Google DeepMind’s AlphaGo, which seems to have mastered the ancient game of Go simply by playing against itself.
Cynthia Murrell, December 19, 2017
Everyone Should Know the Term Cognitive Computing
December 19, 2017
Cognitive computing is a term everyone in the AI world should already be familiar with. If not, it’s time for a crash course. This is the DNA of machine learning and it is a fascinating field, as we learned from a recent Information Age story, “RIP Enterprise Search –AI-Based Cognitive Insight is the Future.”
According to the story:
The future of search is linked directly to the emergence of cognitive computing, which will provide the framework for a new era of cognitive search. This recognizes intent and interest and provides structure to the content, capturing more accurately what is contained within the text.
Context is king, and the four key (NOTE: We only included the most important two) elements of context detection are as follows:
Who – which user is looking for information? What have they looked for previously and what are they likely to be interested in finding in future? Who the individual is key as to what results are delivered to them.
What – the nature of the information is also highly important. Search has moved on from structured or even unstructured text within documents and web pages. Users may be looking for information in any number of different forms, from data within databases and in formats ranging from video and audio, to images and data collected from the internet-of-things (IOT).
Who and what is incredibly important, but that might be putting the cart before the horse. First, we must convince CEOs how important AI is to their business…any business. Thankfully, folks like Huffington Post are already ahead of us and rallying the troops.
Patrick Roland, December 19, 2017
Google Privacy Violation Round Up
December 18, 2017
Concerned about Google’s devil-may-care approach to some privacy issues? I am not. I love the Google. I was dismayed when I read the critical “real” news story “ “Google’s Privacy Practices Are A Matter Of Public Concern.” Read the article and see if you agree that Google really wandered off the privacy reservation with these alleged actions:
- Using the Safari workaround to suck data from Apple iPhones in the UK
- The allegations by the Spanish Data Protection Commission that Google “illegally” used data gathered by its street view service
- The allegation that Google tracked user locations even if the feature had been disabled by the owner of the phone.
Here in Harrod’s Creek we want the Internet to be more Googley. The article appears to take a different view.
Stephen E Arnold, December 18, 2017
Compare Two Devices Within Google Search Results
December 18, 2017
Is Google chasing Consumer Reports now? A very brief write-up at Android Police reveals, “Google Search Can Now Compare Specifications Between Devices and Highlight Differences.” Reporter Corbin Davenport writes:
Google occasionally adds new features to its web search or makes design changes, sometimes without a public announcement. Most recently, Google began rolling out a rounded interface to the mobile search. Now, the company appears to be testing a new comparison feature. For some users, searching for two devices with ‘vs’ in the middle (for example, ‘Pixel 2 vs Pixel 2 XL’) brings up a new comparison chart. A few rows are visible on the main results, and tapping the blue button expands it to show every detail. There’s even a mode to highlight differences between the two. It doesn’t seem to work with three or more devices, only two.
I cannot say whether the feature has been rolled out across the board as of this writing, but it did work on my Android phone. What else does Google have up its sleeve?
Cynthia Murrell, December 18, 2017
Bing Feverishly Tries to Catch Google
December 18, 2017
Google’s kid brother, Bing, has been trying to get the world’s attention basically since its inception. However, the king of search is a tough one to upstage. Bing thinks it has a bright idea on how to best Google, as we discovered in a recent eWeek story, “Microsoft Bing Delivers More ‘Birdseye’ Views of Points of Interest.”
According to the story, Bing thinks the answer lies in their mapping option,
Bird’s Eye uses oblique imagery processing technology to provide detail-packed views that can help travelers navigate their surroundings by sight.
Oblique imagery is a great complement to Aerial 2D imagery because it has much more depth and provides a view of your destination that is more familiar and in line with what people expect,” stated Microsoft Bing staffers in a blog post. “You can see Bird’s Eye imagery in Bing Maps, and this view can offer a better context for navigation because building facades can be used as landmarks.
It’s admirable that Bing is trying to outdo Google, but more detailed maps are probably not the way to go about it. At the end of the day, it all comes down to search power and Bing just doesn’t have it. Google has such a foothold in the market that the competition looks pretty silly by comparison, like how Firefox and Yahoo recently sued one another.
Patrick Roland, December 18, 2017
The Future Is Search. Hmmm
December 17, 2017
I read an unusual chunk of content marketing. Navigate to “In the Rush to Big Data, We Forgot about Search.” Who’s the “we”? I think the “we” are customers who are migrating next generation information access systems. Lawyers have relativity. Manufacturers have SAP and Dassault solutions. Folks without much faith in commercial search vendors have Elasticsearch or low-cost systems which deliver a list of results which match a query. The “we”, therefore, seems to refer to the Lucid Imagination outfit now doing business as Lucidworks.
The write up explains that “we need to look at search to be the glue that lets us find the data and analyze it together no matter where it lives.”
That sounds super.
I think there are companies delivering this type of service as they have been for a number of years.
The reason is that vendors who are anchored in search and retrieval like Lucidworks have been bypassed.
In Dark Cyber I write about a stealthy outfit called Blackdot. The company complements the Relativity eDiscovery platform. Sure, there’s a search function, but Relativity does analytics, clustering, and functions which fit the needs of those engaged in eDiscovery. Search is part of the game, which for big cases, involves big data.
Blackdot enhances Relativity. You can learn about some of the functions of this company in the December 26, 2017, Dark Cyber video program.
So what?
The so what is that the services provided by Relativity and Blackspot deliver high value outputs that provide outputs which are immediately useful to analysts, investigators, lawyers, and others who use the integrated systems to solve problems.
A company which wants to deliver this type of service is likely wade into high water and thrash for purchase. The reason is that building a solution from open source tools and home brew scripts is a tough job.
Specialists have been using open source and proprietary code to roll out information access solutions. Relativity is just one example. By the way, Relativity has been plugging away for more than a decade.
A column which makes a case for a customer to let a vendor of open source search build from ground zero a next generation information access solution is going to be a vendor with a smile. However, once the solution fails to meet expectations, those smiles will turn to frowns.
Maybe that’s why Lucidworks has burned through one original founder, several presidents, and $59 million?
Search is a utility. It is not a headliner. Search works when it complements higher value functionality such as those delivered by Relativity and Blackdot or any of the other firms we track for our CyberOSINT research.
Search had its fling, but the glory days faded. When we look at the landscape of enterprise search or Big Data for that matter, we see winners. From our vantage point in Harrod’s Creek, the company leading the much smaller search parade is Elastic. Yep, it’s Lucene, but it has a following.
Guess who one of the followers is. Give up. Lucidworks. The technology is based on Lucene.
Selling consulting services is one thing. Selling search is another.
Today’s forward looking companies want next generation access, and they can get it from dozens of vendors. No starting from scratch. Sign a deal and begin processing data (big or small).
I highlighted this statement from the write up:
So if you move some of your data to SaaS solutions, move some of your data to PaaS solutions, move some of your data to IaaS solutions and across multiple vendors’ cloud platforms while maintaining some of your data behind the firewall—yeah, no one is going to find anything!
Sure. Solve problems. Don’t create them. One can search for solutions using a search engine. Let me know how that works out for your next big decision which you have to make in 10 seconds or less.
Stephen E Arnold, December 17, 2017
Quick Question: Why Not Loon Balloons, Google?
December 16, 2017
I read “Google Is Using Light Beam Tech to Connect Rural India to the Internet.” I understand. But the question just hangs there like a hot air balloon on a still day:
Why not use the vaunted Loon balloons?
I have an idea or two. What do you think about cost, complexity, and the weather? Yep, weather. As in weather balloons.
Does this pop the loon balloon big idea or just shine light on a loon balloon?
Stephen E Arnold, December 16, 2017
AI in China: Insiders and Outsiders
December 15, 2017
Google is trying to scramble in China’s artificial intelligence market. Several years ago, Google wanted China to “change.” Now it looks as if Google has figured out that it has to conform in order to catch up with other outfits in the Middle Kingdom.
Case in point: Navigate to “Li Ka-Shing Bets on Hong Kong AI Start-Up to Parse Chinese Call Centre Industry’s Tower of Babel.” Mr. Ka-Shing is an important figure and rumor has it that he is associated with some powerful government figures in China. He also has money, telecommunications, shipping, and other interests to help him pay his bills.
The funding of Fano Labs via Horizon Ventures is important in my opinion. For outfits like Google, the best and brightest of the Chinese AI experts may find their future in companies similar to those Mr. Ka-Shing finds “interesting.”
Outsiders? Nope, insiders. The difference is important when it comes to big deals in China in my experience.
Stephen E Arnold, December 14, 2017
-
- Subscribe to Beyond Search
Feature archive
News archive
-
