Towards a Bio-Internet of Things?

Seems we are already part of that, if we like it or not, but here is some more

The scientists who are creating a bio-internet of things in Technology Review

The internet of things connects devices across the globe. Now researchers are considering how bacteria can join the network.

Imagine designing the perfect device for the internet of things. What functions must it have? For a start, it must be able to communicate, both with other devices and with its human overlords. It must be able to store and process information. And it must monitor its environment with a range of sensors. Finally, it will need some kind of built-in motor.

There is no shortage of devices that have many of these features. Most are based on widely available, low-cost devices such as Raspberry Pis, Arduino boards, and the like.

But another set of machines with similar functions is much more plentiful, say Raphael Kim and Stefan Poslad at Queen Mary University of London in the UK. They point out that bacteria communicate effectively and have built-in engines and sensors, as well as powerful information storage and processing architecture.

And that raises an interesting possibility, they say. Why not use bacteria to create a biological version of the internet of things? Today, in a call to action, they lay out some of the thinking and the technologies that could make this possible.  ... " 

Speeding up Biological Imaging

An example of the sharing of methodology to create algorithms.  Note also the replacement and augmentation of human process.

Researchers Use Algorithm From Netflix Challenge to Speed Up Biological Imaging 
Optical Society of America

Scientists at the Ecole Normale Superieure in France have repurposed an algorithm developed for Netflix's 2009 movie preference prediction challenge for high-speed acquisition of classical Raman spectroscopy biological-tissue images. The researchers demonstrated imaging speeds of a few tens of seconds for an image that would usually take minutes to obtain, and they think sub-second speeds could be realized in the future. Said Ecole Normale Superieure's Hilton de Aguiar, "We combined compressive imaging with fast computer algorithms that provide the kind of images clinicians use to diagnose patients, but rapidly and without laborious manual post-processing." The researchers replaced costly, slow cameras used in conventional setups with a spatial light modulator, which selects groups of wavelengths identified by a single-pixel detector, compressing images as they are captured. This allowed the team to use a portion of the data typically required for non-invasive Raman spectroscopy, and employ the Netflix algorithm to fill in the missing information .... "

An Architecture for Intelligence?

Is there an underlying model for intelligence?    Is it a structurally simple enough one that we could readily convert into code, we could create something that thinks like the brain?    Still unknown.  Also looking for that secret part we still don't know.

Could this then lead use for AGI      Artificial General Intelligence, AKA "Strong AI"  or   "the intelligence of a machine that could successfully perform any intellectual task that a human being can"?  We don't know that either,  but we know the brain thinks, and its made of things we can dissect piece by piece  (Technical)

The Genius Neuroscientist who might hold the key to True AI.  By Shaun Raviv in Wired

See also:  Karl Friston   https://en.wikipedia.org/wiki/Karl_J._Friston

And further: https://en.wikipedia.org/wiki/Free_energy_principle

The free energy principle tries to explain how (biological) systems maintain their order (non-equilibrium steady-state) by restricting themselves to a limited number of states.[1] It says that biological systems minimise a free energy functional of their internal states, which entail beliefs about hidden states in their environment. The implicit minimisation of variational free energy is formally related to variational Bayesian methods and was originally introduced by Karl Friston as an explanation for embodied perception in neuroscience,[2] where it is also known as active inference.

Markov Blanket   https://en.wikipedia.org/wiki/Markov_blanket

Bio Bots

Like the idea of combining biological cells and digital.    At a kind of fundamental layer.  A synthetic Biology of sorts.

Now You Can 'Build Your Own' Bio-Bot
By University of Illinois News Bureau
February 16, 2017

Researchers at the University of Illinois at Urbana-Champaign have released their protocol for designing and building "bio-bots" powered by muscle cells and controlled with light and electrical signals.

They say the bio-bots are less than a centimeter in size and made of flexible three-dimensionally (3D)-printed hydrogels and living cells. ....  "

In 2012, the researchers demonstrated the bio-bots' ability to move on their own, powered by contracting heart cells from rats. A light-responsive skeletal muscle cell was genetically engineered to contract when stimulated by pulses of a certain wavelength of blue light. The skeletal muscle tissue was then coupled to a 3D-printed skeleton that moves in the direction of the optical pulses. ... "

The Origami Revolution

An informative video on PBS today regarding the use of Origami as a design methodology, how research on origami based models is progressing and a number of good examples.  Very well done.   We explored this for some packaging innovation proposals. Note this means of access to the video appears to expire on March 1,  2017.

The Origami Revolution  PBS 
Video duration: 53:50 Aired: 02/15/17 Expires: 03/01/17
Rating: NR Video has closed captioning. .... 

Engineers are using origami to design drugs, micro-robots, and future space missions. ... . "

Note also on Origami at MIT.  Links to free MIT talks and materials via Erik Demaine.

A New Biology

Including the work of a biological game theorist.

From matchbook-sized models of living human organs to the surprising alternative-energy implications of symbiotic giant clams, the work of three new faculty members represents the changing face of bioscience at Penn.  ... By  Trey Popp

Biofactories of the Future

Pointing to a Nature article of interest. " ..... From an evolutionary perspective, yeast has no business producing a pain killer. But by re-engineering the microbe's genome, Christina Smolke at Stanford University in California has made it do precisely that. ...  

Future of Ethics of People and Machines

Cambridge University looks at AI ethics in the interaction of people and machines.

The future of intelligence: Cambridge University launches new centre to study AI and the future of humanity ... 

The University of Cambridge is launching a new research centre, thanks to a £10 million grant from the Leverhulme Trust, to explore the opportunities and challenges to humanity from the development of artificial intelligence. 

Machine intelligence will be one of the defining themes of our century, and the challenges of ensuring that we make good use of its opportunities are ones we all face together
Huw Price

Human-level intelligence is familiar in biological “hardware” – it happens inside our skulls. Technology and science are now converging on a possible future where similar intelligence can be created in computers. ... " 

Processes of Memory and Learning. Machine Learning?

Several Blogs have recently picked up on the processes of learning.  Just this past week there have been a number of advances revealed on linking analytic and biomimicry processes.   Notably the use of Bayesian methods.  See this recent example.   In the Guardian a look at some classic studies of learning.

It should be noted that 'Machine Learning' (ML), as currently defined, is more about statistically based pattern recognition, than the kind of learning mentioned here.   A machine learning method can be used to determine patterns in data, and then those patterns could be stored away for later access and reference.  But that kind of full ML process is not usual today.   It should be more often considered.

'Deep Learning', is another term much in the news, but it is usually applied to more narrowly focused problems, like image recognition.   But it does use biologically inspired math constructs like neural networks.

Biologically Inspired Question Answering

 Via Jim Spohrer.    See the previous CSIG talk on this work.

In Kurzweil AI: IBM’s Watson shown to enhance human-computer co-creativity, support biologically inspired design ... Watson Engagement Advisor AI system was trained to "learn" about biologically inspired design from biology articles, then answer questions.

Georgia Institute of Technology researchers, working with student teams, trained a cloud-based version of IBM’s Watson called the Watson Engagement Advisor to provide answers to questions about biologically inspired design (biomimetics), a design paradigm that uses biological systems as analogues for inventing technological systems.

Ashok Goel, a professor at Georgia Tech’s School of Interactive Computing who conducts research on computational creativity. In an experiment, he used this version of Watson as an “intelligent research assistant” to support teaching about biologically inspired design and computational creativity in the Georgia Tech CS4803/8803 class on Computational Creativity in Spring 2015. Goel found that Watson’s ability to retrieve natural language information could allow a novice to quickly “train up” about complex topics and better determine whether their idea or hypothesis is worth pursuing.  ... " 

Neural Networks and Deep Learning

Neural Networks and Deep Learning is a free online book. The book will teach you about:  Neural networks, a beautiful biologically-inspired programming paradigm which enables a computer to learn from observational data Deep learning, a powerful set of techniques for learning in neural networks  ...   " 

Neuromorphic Chips

In Wired: 48 million neurons mimic the brain of a small rodent.  Increasingly we are looking at how to directly model the biological.   Is it better to mimic biological systems or to directly model them?   Also in Linkedin.

Center for Neural Decision Making

Was referred to this recently.  I like the broader view of looking at decision making in general, not just that which can be detected by brain science.

"... The Center for Neural Decision Making at the Fox School of Business (At Temple University) investigates the neurobiological bases of human behavior, preference formation, and decision making. .... 

CNDM research has recently been featured in several news articles, including  in Forbes: Neuromarketing: Pseudoscience No More  (February 24th, 2015) and  in Science Magazine:  What will be the best Super Bowl commercial? Science may have the answer (January 27th, 2015).  .... "   (Links at the site)

We followed the super bowl ad metric for some years here.

A number of interesting publications are pointed to.  Part of @foxschool, but there appears to be no stream for the Neural Decision Making work except at the site link above.

Distributed Information Processing

A lengthy article that gives cues to how we can use biological models for computation.  Video.
"... Biological systems, ranging from the molecular to the cellular to the organism level, are distributed and in most cases operate without central control. Such systems must solve information processing problems that are often very similar to problems faced by computational systems, including coordinated decision making,29 leader election,2 routing and navigation,52 and more.42 .. "

Another Style of Artificial Intelligence

Another look at Numenta

Numenta has developed a cohesive theory, core software technology, and numerous applications all based on principles of the neocortex. This technology lays the groundwork for the new era of machine intelligence. Our innovative work delivers breakthrough capabilities and demonstrates that a computing approach based on biological learning principles will make possible a new generation of capabilities not possible with today’s programmed computers. ... "

Previously about Numenta.  And in the Wikipedia.

IBM Rival Sentient

An AI rival to understand: Sentient: With some emphasis on big data and genetic methods.  And the direct use of biomimicry through the use of genetic algorithms, an area we experimented in.

" ... Sentient was inspired because of its team’s work on Siri, which exposed them to “actual real applications of machine learning and artificial intelligence,” Mr. Blondeau said. They saw what they thought was a unique opportunity to combine that technology “with what the Internet gives us now in terms of the ability to reach and harness enormous amounts of compute—things that couldn’t be dreamt of 10 years ago, and could be done five years ago but nobody had done that.”

He said Sentient combines technologies in evolutionary computation, which mimics in software the way biological life evolved on Earth, and deep learning, which looks at the way nervous systems are architected and work. These technologies are used either independently or together and are scaled across millions of nodes.... " 

Biologically Inspired Design

Attended a talk today in the Cog Sci Institute on the status of work being done at Ga Tech on Biologically Inspired design, or Biomimicry.  Given by Prof. Ashok Goel    Most often examples in this space look at how designs in nature can be used to address specific human engineering problems.  Most of what they are doing today is trying to understand how human knowledge about biology can be retrieved to address engineering requirements.  The problem is that engineers and biologists don't speak the same technical language.  Also, we need to understand how to search and reason by analogy in both domains.  The extension of analogy is a form of creativity.  We researched reasoning by analogy when addressing consumer needs.   This can then be linked to cognition, as part of Human centered computing. All this is a crucial part of AI.  There is much more work to be done.

Talk slides: https://www.slideshare.net/secret/9S42InuTABn0qY

Agent Modeling and Health Care Data

This reports on work done with Argonne National Labs, known for their work with agent based simulation models or ABMs.   We used similar models with Argonne for evaluating product introduction.

" ... Now, a collaboration between researchers at the Computation Institute and University of Chicago Medicine & Biological Sciences will create a new, information-rich tool for assessing and refining health care innovations and policies. With a $3 million grant from the National Institutes of Health, scientists from the Social and Behavioral Systems Group at Argonne National Laboratory will build an agent-based model to evaluate CommunityRx, a health information technology project underway in several South Side clinics.

Beyond providing valuable new information about the broader impact of CommunityRx, the researchers hope the model will lay the foundation for a new computational testing ground for health care and policy programs. ... " 

Naturally Intelligent Interaction

Recently received, The BabyX piece at the link is very interesting.    " ... One of my gigs is commercial licensing advisor to Auckland UniServices working with Dr. Mark Sagar Director ​of The Laboratory for Animate Technologies  which is pioneering biologically based methods to give computers the power of expression and naturally intelligent interaction. Check out BabyX ​which is a computer generated psychobiological simulation which learns and interacts in real time with computational neuroscience models of neural systems.‏ ... Steve Ardire  ... "

Finding Hidden Laws

The Santa Fe Institute on  " ... Finding the hidden laws that pervade complex biological & social phenomena ... "