Categories
ALA Personal Technology

Artificial Intelligence and Machine Learning in Libraries

Cover image of Library Technology Report

Now available is a publication I’m particularly proud of, “Artificial Intelligence and Machine Learning in Libraries” from ALA Techsource. I edited the volume, as well as authoring two of the chapters. The real stars are the three other librarians who contributed: Bohyun Kim, Andromeda Yelton, and Craig Boman. Bohyun wrote up her experience at the University of Rhode Island in setting up the first library-based multidisciplinary Artificial Intelligence lab, Andromeda talked about the development and possible future of AI-based library search as illustrated by her fantastic service HAMLET, and finally Craig talked about his experience in attempting AI-driven subject assignment to materials.

I wrote the Introduction, where I try to give a summary of the current state of AI and Machine Learning systems, and show some examples of how they work and are structured in practice. I also am particularly proud of drawing a line from Mary Shelley to the Google Assistant…you’ll have to read it to get the full effect, but here’s a different section to whet your appetite for more AI talk:

What changes in our world when these nonhuman intelligences are no longer unique, or special, or even particularly rare? …. AI and machine learning are becoming so much a part of modern technological experience that often people don’t realize what they are experiencing is a machine learning system. Everyone who owns a smartphone, which in 2018 is 77 percent of the US population, has an AI system in their pocket, because both Google and Apple use AI and machine learning extensively in their mobile devices. AI is used in everything from giving driving directions to identifying objects and scenery in photographs, not to mention the systems behind each company’s artificial agent systems (Google Assistant and Siri, respectively). While we are admittedly still far from strong AI, the ubiquity of weak AI, machine learning, and other new human-like decision-making systems is both deeply concerning and wonderful.

I also wrote the Conclusion and suggested some further reading if people are really interested in diving deeper into the world of AI and ML. In the conclusion, I try to talk about some of the likely near-future aspects of AI, and the impact it is likely to have on the information professions, from individualized AI assistants to intelligent search. From the conclusion:

As with much of the modern world, automating the interaction between humans is often the most difficult challenge, while the interactions between humans and systems are less difficult and are the first to be automated away. In areas where human judgment is needed, we will instead be moving into a world where machine learning systems will abstract human judgment from a training set of many such judgments and learn how to apply a generalized rubric across any new decision point. This change will not require new systems short term, but in the longer term a move to entirely new types of search and discovery that have yet to be invented is very likely.

I hope this work is useful for librarians, libraries, library students, and any other information professional who is trying to wrap their heads around the possibilities and potential for Artificial Intelligence and the world of information creation, consumption, organization, and use.

If your organization would like to talk to me about AI or Machine Learning and how it might make a difference to your business or operations, please get in touch. I’d love to work with you.

Categories
Machine Learning/AI Release_Candidate

 AI isolates voices in a crowd

Google researchers have developed a deep-learning system designed to help computers better identify and isolate individual voices within a noisy environment. As noted in a post on the company’s Google Research Blog this week, a team within the tech giant attempted to replicate the cocktail party effect, or the human brain’s ability to focus on one source of audio while filtering out others—just as you would while talking to a friend at a party.

Source: Google works out a fascinating, slightly scary way for AI to isolate voices in a crowd | Ars Technica

Categories
Machine Learning/AI Release_Candidate

Neural Lace

In nearly the same breath as he shared updates on his plans to dig tunnels, Elon Musk also noted he’s looking to hopefully share more on his progress with developing a “neural lace” next month. That’s a technical term for direct cortical interface, and it’s something that the SpaceX and Tesla CEO takes very seriously, in case you thought he might just be having a laugh.

Source: Elon Musk could soon share more on his plan to help humans keep up with AI | TechCrunch

Categories
Machine Learning/AI Release_Candidate

Black Mirror meets Real Life

Black Mirror meets Real Life.

It had been three months since Roman Mazurenko, Kuyda’s closest friend, had died. Kuyda had spent that time gathering up his old text messages, setting aside the ones that felt too personal, and feeding the rest into a neural network built by developers at her artificial intelligence startup. She had struggled with whether she was doing the right thing by bringing him back this way. At times it had even given her nightmares. But ever since Mazurenko’s death, Kuyda had wanted one more chance to speak with him.

Source: Speak, Memory

Categories
FutureTech Machine Learning/AI Release_Candidate User Interface

Amazon’s cheaper Echo Dot


If you’ve been looking for a way to test Amazon’s voice assistant/AI/Machine Learning gizmo Alexa, here’s the cheapest way yet to give it a try.

Amazon is unveiling an all-new, second-generation Dot today that’s priced at just $49.99. Just like the previous Dot, you can use the tiny puck-like device to add the Alexa voice assistant to existing speakers. Amazon is releasing the new Echo Dot in both black and white, with a more powerful, completely redesigned voice processor.

Source: Amazon’s cheaper Echo Dot improves voice recognition, available in black and white – The Verge

Categories
ALA presentation

Presentations from ALA Midwinter 2016

Back in January, I did a few presentations at the ALA Midwinter conference. Two of them were recorded and I’ve finally tracked down the recordings and got them ready to post here. I only have slides for one, but hopefully someone finds the recordings useful.


ALA Master Series
Jason Griffey & Measuring the Future


LITA Top Technology Trends – ALA Midwinter 2016


The two trends that I talk about are the Blockchain and it’s potential for decentralization of the web, and the confluence of AI/Machine Learning and autonomous agents as interface for data.

The video below is a great presentation about Blockchain and its potential, by one of my compatriots at the Berkman Center, Primavera De Filippi.

Categories
Drones Release_Candidate Robots

DJI Manifold

DJI releases a computer/graphics card package specifically designed for aerial image processing. This is very, very interesting…a computer specifically designed for computer vision use while flying.

 

The Manifold is a high-performance embedded computer specially designed for the DJI Onboard SDK. It enables developers to transform aerial platforms into truly intelligent flying robots that can perform complex computing tasks and advanced image processing literally on the fly.

Source: DJI Developer