Google rolls out new ‘smart reply’ machine-learning email software to more than 1 billion Gmail mobile users

A smarter version of Smart Reply (credit: Google Research)

Google is rolling out an enhanced version of its “smart reply” machine-learning email software to “over 1 billion Android and iOS users of Gmail,” Google CEO Sundar Pichai said today (May 17, 2017) in a keynote at the annual Google I/O conference.

Smart Reply suggests up to three replies to an email message — saving you typing time, or giving you time to think through a better reply. Smart Reply was previously only available to users of Google Inbox (an app that helps Gmail users organize their email messages and reply efficiently).

Hierarchical model

Developed by a team headed by Ray Kurzweil, a Google director of engineering, “the new version of Smart Reply increases the percentage of usable suggestions and is much more algorithmically efficient than the original system,” said Kurzweil in a Google Research blog post with research colleague Brian Strope today. “And that efficiency now makes it feasible for us to provide Smart Reply for Gmail.”

A hierarchy of modules (credit: Google Research)

The team was inspired by how humans understand languages and concepts, based on hierarchical models of language, Kurzweil and Strope explained. The new approach uses “hierarchies of modules, each of which can learn, remember, and recognize a sequential pattern,” as described in Kurzweil’s 2012 book, How to Create a Mind.

For example, a sentence like “That interesting person at the cafe we like gave me a glance” is difficult to interpret. Was it a positive or negative gesture? “But “given enough examples of language, a machine learning approach can discover many of these subtle distinctions,” they write.

Best of MOOGFEST 2017

The Moogfest four-day festival in Durham, North Carolina next weekend (May 18 — 21) explores the future of technology, art, and music. Here are some of the sessions that may be especially interesting to KurzweilAI readers. Full #Moogfest2017 Program Lineup.

Culture and Technology

(credit: Google)

The Magenta by Google Brain team will bring its work to life through an interactive demo plus workshops on the creation of art and music through artificial intelligence.

Magenta is a Google Brain project to ask and answer the questions, “Can we use machine learning to create compelling art and music? If so, how? If not, why not?” It’s first a research project to advance the state-of-the art and creativity in music, video, image and text generation and secondly, Magenta is building a community of artists, coders, and machine learning researchers.

The interactive demo will go through a improvisation along with the machine learning models, much like the Al Jam Session. The workshop will cover how to use the open source library to build and train models and interact with them via MIDI.

Technical reference: Magenta: Music and Art Generation with Machine Intelligence


TEDx Talks | Music and Art Generation using Machine Learning | Curtis Hawthorne | TEDxMountainViewHighSchool


Miguel Nicolelis (credit: Duke University)

Miguel A. L. Nicolelis, MD, PhD will discuss state-of-the-art research on brain-machine interfaces, which make it possible for the brains of primates to interact directly and in a bi-directional way with mechanical, computational and virtual devices. He will review a series of recent experiments using real-time computational models to investigate how ensembles of neurons encode motor information. These experiments have revealed that brain-machine interfaces can be used not only to study fundamental aspects of neural ensemble physiology, but they can also serve as an experimental paradigm aimed at testing the design of novel neuroprosthetic devices.

He will also explore research that raises the hypothesis that the properties of a robot arm, or other neurally controlled tools, can be assimilated by brain representations as if they were extensions of the subject’s own body.

Theme: Transhumanism


Dervishes at Royal Opera House with Matthew Herbert (credit: ?)

Andy Cavatorta (MIT Media Lab) will present a conversation and workshop on a range of topics including the four-century history of music and performance at the forefront of technology. Known as the inventor of Bjork’s Gravity Harp, he has collaborated on numerous projects to create instruments using new technologies that coerce expressive music out of fire, glass, gravity, tiny vortices, underwater acoustics, and more. His instruments explore technologically mediated emotion and opportunities to express the previously inexpressible.

Theme: Instrument Design


Berklee College of Music

Michael Bierylo (credit: Moogfest)

Michael Bierylo will present his Modular Synthesizer Ensemble alongside the Csound workshops from fellow Berklee Professor Richard Boulanger.

Csound is a sound and music computing system originally developed at MIT Media Lab and can most accurately be described as a compiler or a software that takes textual instructions in the form of source code and converts them into object code which is a stream of numbers representing audio. Although it has a strong tradition as a tool for composing electro-acoustic pieces, it is used by composers and musicians for any kind of music that can be made with the help of the computer and has traditionally being used in a non-interactive score driven context, but nowadays it is mostly used in in a real-time context.

Michael Bierylo serves as the Chair of the Electronic Production and Design Department, which offers students the opportunity to combine performance, composition, and orchestration with computer, synthesis, and multimedia technology in order to explore the limitless possibilities of musical expression.


Berklee College of Music | Electronic Production and Design (EPD) at Berklee College of Music


Chris Ianuzzi (credit: William Murray)

Chris Ianuzzi, a synthesist of Ciani-Musica and past collaborator with pioneers such as Vangelis and Peter Baumann, will present a daytime performance and sound exploration workshops with the B11 braininterface and NeuroSky headset–a Brainwave Sensing Headset.

Theme: Hacking Systems


Argus Project (credit: Moogfest)

The Argus Project from Gan Golan and Ron Morrison of NEW INC is a wearable sculpture, video installation and counter-surveillance training, which directly intersects the public debate over police accountability. According to ancient Greek myth, Argus Panoptes was a giant with 100 eyes who served as an eternal watchman, both for – and against – the gods.

By embedding an array of camera “eyes” into a full body suit of tactical armor, the Argus exo-suit creates a “force field of accountability” around the bodies of those targeted. While some see filming the police as a confrontational or subversive act, it is in fact, a deeply democratic one.  The act of bearing witness to the actions of the state – and showing them to the world – strengthens our society and institutions. The Argus Project is not so much about an individual hero, but the Citizen Body as a whole. In between one of the music acts, a presentation about the project will be part of the Protest Stage.

Argus Exo Suit Design (credit: Argus Project)

Theme: Protest


Found Sound Nation (credit: Moogfest)

Democracy’s Exquisite Corpse from Found Sound Nation and Moogfest, an immersive installation housed within a completely customized geodesic dome, is a multi-person instrument and music-based round-table discussion. Artists, activists, innovators, festival attendees and community engage in a deeply interactive exploration of sound as a living ecosystem and primal form of communication.

Within the dome, there are 9 unique stations, each with their own distinct set of analog or digital sound-making devices. Each person’s set of devices is chained to the person sitting next to them, so that everybody’s musical actions and choices affect the person next to them, and thus affect everyone else at the table. This instrument is a unique experiment in how technology and the instinctive language of sound can play a role in the shaping of a truly collective unconscious.

Theme: Protest


(credit: Land Marking)

Land Marking, from Halsey Burgund and Joe Zibkow of MIT Open Doc Lab, is a mobile-based music/activist project that augments the physical landscape of protest events with a layer of location-based audio contributed by event participants in real-time. The project captures the audioscape and personal experiences of temporary, but extremely important, expressions of discontent and desire for change.

Land Marking will be teaming up with the Protest Stage to allow Moogfest attendees to contribute their thoughts on protests and tune into an evolving mix of commentary and field recordings from others throughout downtown Durham. Land Marking is available on select apps.

Theme: Protest


Taeyoon Choi (credit: Moogfest)

Taeyoon Choi, an artist and educator based in New York and Seoul, who will be leading a Sign Making Workshop as one of the Future Thought leaders on the Protest Stage. His art practice involves performance, electronics, drawings and storytelling that often leads to interventions in public spaces.

Taeyoon will also participate in the Handmade Computer workshop to build a1 Bit Computer, which demonstrates how binary numbers and boolean logic can be configured to create more complex components. On their own these components aren’t capable of computing anything particularly useful, but a computer is said to be Turing complete if it includes all of them, at which point it has the extraordinary ability to carry out any possible computation. He has participated in numerous workshops at festivals around the world, from Korea to Scotland, but primarily at the School for Poetic Computation (SFPC) — an artist run school co-founded by Taeyoon in NYC. Taeyoon Choi’s Handmade Computer projects.

Theme: Protest


(credit: Moogfest)

irlbb from Vivan Thi Tang, connects individuals after IRL (in real life) interactions and creates community that otherwise would have been missed. With a customized beta of the app for Moogfest 2017, irlbb presents a unique engagement opportunity.

Theme: Protest


Ryan Shaw and Michael Clamann (credit: Duke University)

Duke Professors Ryan Shaw, and Michael Clamann will lead a daily science pub talk series on topics that include future medicine, humans and anatomy, and quantum physics.

Ryan is a pioneer in mobile health—the collection and dissemination of information using mobile and wireless devices for healthcare–working with faculty at Duke’s Schools of Nursing, Medicine and Engineering to integrate mobile technologies into first-generation care delivery systems. These technologies afford researchers, clinicians, and patients a rich stream of real-time information about individuals’ biophysical and behavioral health in everyday environments.

Michael Clamann is a Senior Research Scientist in the Humans and Autonomy Lab (HAL) within the Robotics Program at Duke University, an Associate Director at UNC’s Collaborative Sciences Center for Road Safety, and the Lead Editor for Robotics and Artificial Intelligence for Duke’s SciPol science policy tracking website. In his research, he works to better understand the complex interactions between robots and people and how they influence system effectiveness and safety.

Theme: Hacking Systems


Dave Smith (credit: Moogfest)

Dave Smith, the iconic instrument innovator and Grammy-winner, will lead Moogfest’s Instruments Innovators program and host a headlining conversation with a leading artist revealed in next week’s release. He will also host a masterclass.

As the original founder of Sequential Circuits in the mid-70s and Dave designed the Prophet-5––the world’s first fully-programmable polyphonic synth and the first musical instrument with an embedded microprocessor. From the late 1980’s through the early 2000’s he has worked to develop next level synths with the likes of the Audio Engineering Society, Yamaha, Korg, Seer Systems (for Intel). Realizing the limitations of software, Dave returned to hardware and started Dave Smith Instruments (DSI), which released the Evolver hybrid analog/digital synthesizer in 2002. Since then the DSI product lineup has grown to include the Prophet-6, OB-6, Pro 2, Prophet 12, and Prophet ’08 synthesizers, as well as the Tempest drum machine, co-designed with friend and fellow electronic instrument designer Roger Linn.

Theme: Future Thought


Dave Rossum, Gerhard Behles, and Lars Larsen (credit: Moogfest)

EM-u Systems Founder Dave Rossum, Ableton CEO Gerhard Behles, and LZX Founder Lars Larsen will take part in conversations as part of the Instruments Innovators program.

Driven by the creative and technological vision of electronic music pioneer Dave Rossum, Rossum Electro-Music creates uniquely powerful tools for electronic music production and is the culmination of Dave’s 45 years designing industry-defining instruments and transformative technologies. Starting with his co-founding of E-mu Systems, Dave provided the technological leadership that resulted in what many consider the premier professional modular synthesizer system–E-mu Modular System–which became an instrument of choice for numerous recording studios, educational institutions, and artists as diverse as Frank Zappa, Leon Russell, and Hans Zimmer. In the following years, worked on developing Emulator keyboards and racks (i.e. Emulator II), Emax samplers, the legendary SP-12 and SP-1200 (sampling drum machines), the Proteus sound modules and the Morpheus Z-Plane Synthesizer.

Gerhard Behles co-founded Ableton in 1999 with Robert Henke and Bernd Roggendorf. Prior to this he had been part of electronic music act “Monolake” alongside Robert Henke, but his interest in how technology drives the way music is made diverted his energy towards developing music software. He was fascinated by how dub pioneers such as King Tubby ‘played’ the recording studio, and began to shape this concept into a music instrument that became Ableton Live.

LZX Industries was born in 2008 out of the Synth DIY scene when Lars Larsen of Denton, Texas and Ed Leckie of Sydney, Australia began collaborating on the development of a modular video synthesizer. At that time, analog video synthesizers were inaccessible to artists outside of a handful of studios and universities. It was their continuing mission to design creative video instruments that (1) stay within the financial means of the artists who wish to use them, (2) honor and preserve the legacy of 20th century toolmakers, and (3) expand the boundaries of possibility. Since 2015, LZX Industries has focused on the research and development of new instruments, user support, and community building.


Science

ATLAS detector (credit: Kaushik De, Brookhaven National Laboratory)

ATLAS @ CERN. The full ATLAS @ CERN program will be led by Duke University Professors Mark Kruse andKatherine Hayles along with ATLAS @ CERN Physicist Steven Goldfarb.

The program will include a “Virtual Visit” to the Large Hadron Collider — the world’s largest and most powerful particle accelerator — via a live video session,  a ½ day workshop analyzing and understanding LHC data, and a “Science Fiction versus Science Fact” live debate.

The ATLAS experiment is designed to exploit the full discovery potential and the huge range of physics opportunities that the LHC provides. Physicists test the predictions of the Standard Model, which encapsulates our current understanding of what the building blocks of matter are and how they interact – resulting in one such discoveries as the Higgs boson. By pushing the frontiers of knowledge it seeks to answer to fundamental questions such as: What are the basic building blocks of matter? What are the fundamental forces of nature? Could there be a greater underlying symmetry to our universe?

“Atlas Boogie” (referencing Higgs Boson):

ATLAS Experiment | The ATLAS Boogie

(credit: Kate Shaw)

Kate Shaw (ATLAS @ CERN), PhD, in her keynote, titled “Exploring the Universe and Impacting Society Worldwide with the Large Hadron Collider (LHC) at CERN,” will dive into the present-day and future impacts of the LHC on society. She will also share findings from the work she has done promoting particle physics in developing countries through her Physics without Frontiers program.

The ATLAS experiment is designed to exploit the full discovery potential and the huge range of physics opportunities that the LHC provides. Physicists test the predictions of the Standard Model, which encapsulates our current understanding of what the building blocks of matter are and how they interact – resulting in one such discoveries as the Higgs boson. By pushing the frontiers of knowledge it seeks to answer to fundamental questions such as: What are the basic building blocks of matter? What are the fundamental forces of nature? Could there be a greater underlying symmetry to our universe?

Theme: Future Thought


Arecibo (credit: Joe Davis/MIT)

In his keynote, Joe Davis (MIT) will trace the history of several projects centered on ideas about extraterrestrial communications that have given rise to new scientific techniques and inspired new forms of artistic practice. He will present his “swansong” — an interstellar message that is intended explicitly for human beings rather than for aliens.

Theme: Future Thought


Immortality bus (credit: Zoltan Istvan)

Zoltan Istvan (Immortality Bus), the former U.S. Presidential candidate for the Transhumanist party and leader of the Transhumanist movement, will explore the path to immortality through science with the purpose of using science and technology to radically enhance the human being and human experience. His futurist work has reached over 100 million people–some of it due to the Immortality Bus which he recently drove across America with embedded journalists aboard. The bus is shaped and looks like a giant coffin to raise life extension awareness.


Zoltan Istvan | 1-min Hightlight Video for Zoltan Istvan Transhumanism Documentary IMMORTALITY OR BUST

Theme: Transhumanism/Biotechnology


(credit: Moogfest)

Marc Fleury and members of the Church of Space — Park Krausen, Ingmar Koch, and Christ of Veillon — return to Moogfest for a second year to present an expanded and varied program with daily explorations in modern physics with music and the occult, Illuminati performances, theatrical rituals to ERIS, and a Sunday Mass in their own dedicated “Church” venue.

Theme: Techno-Shamanism

#Moogfest2017

Do robots creep you out?

Which of these presentation methods make the robot look most real: live, VR, 3D TV, or 2D TV? (credit: Constanze Schreiner/University of Koblenz-Landau, Martina Mara/Ars Electronica Futuerlab, and Markus Appel/ University of Wurzburg)

How do you make humanoid robots look least creepy? With increasing use of industrial (and soon, service robots), it’s a good question.

Researchers at the University of Koblenz-Landau, University of Wurzburg, and Arts Electronica Futurelab decided to find out with an experiment. They created a skit with a human actor and the Roboy robot, and presented scripted human-robot interactions (HRIs), using four types of presentations: live, virtual reality (VR), 3D TV, and 2D TV. Participants saw Roboy assisting the human in organizing appointments, conducting web searches, and finding a birthday present for the human’s mother.

People who watched live interactions with the robot were most likely to consider the robot as real, followed by viewing the same interaction via VR. Robots presented in VR also scored high in human likeness, but lower than in the live presentation.

The researchers will present their findings at the 67th Annual Conference of the International Communication Association in San Diego, CA, May 25–29, 2017.

 

A deep-learning tool that lets you clone an artistic style onto a photo

The Deep Photo Style Transfer tool lets you add artistic style and other elements from a reference photo onto your photo. (credit: Cornell University)

“Deep Photo Style Transfer” is a cool new artificial-intelligence image-editing software tool that lets you transfer a style from another (“reference”) photo onto your own photo, as shown in the above examples.

An open-access arXiv paper by Cornell University computer scientists and Adobe collaborators explains that the tool can transpose the look of one photo (such as the time of day, weather, season, and artistic effects) onto your photo, making it reminiscent of a painting, but that is still photorealistic.

The algorithm also handles extreme mismatch of forms, such as transferring a fireball to a perfume bottle. (credit: Fujun Luan et al.)

“What motivated us is the idea that style could be imprinted on a photograph, but it is still intrinsically the same photo, said Cornell computer science professor Kavita Bala. “This turned out to be incredibly hard. The key insight finally was about preserving boundaries and edges while still transferring the style.”

To do that, the researchers created deep-learning software that can add a neural network layer that pays close attention to edges within the image, like the border between a tree and a lake.

The software is still in the research stage.

Bala, Cornell doctoral student Fujun Luan, and Adobe collaborators Sylvian Paris and Eli Shechtman will present their paper at the Conference on Computer Vision and Pattern Recognition on July 21–26 in Honolulu.

This research is supported by a Google Faculty Re-search Award and NSF awards.


Abstract of Deep Photo Style Transfer

This paper introduces a deep-learning approach to photographic style transfer that handles a large variety of image content while faithfully transferring the reference style. Our approach builds upon the recent work on painterly transfer that separates style from the content of an image by considering different layers of a neural network. However, as is, this approach is not suitable for photorealistic style transfer. Even when both the input and reference images are photographs, the output still exhibits distortions reminiscent of a painting. Our contribution is to constrain the transformation from the input to the output to be locally affine in colorspace, and to express this constraint as a custom fully differentiable energy term. We show that this approach successfully suppresses distortion and yields satisfying photorealistic style transfers in a broad variety of scenarios, including transfer of the time of day, weather, season, and artistic edits.


Deep learning-based bionic hand grasps objects automatically

British biomedical engineers have developed a new generation of intelligent prosthetic limbs that allows the wearer to reach for objects automatically, without thinking — just like a real hand.

The hand’s camera takes a picture of the object in front of it, assesses its shape and size, picks the most appropriate grasp, and triggers a series of movements in the hand — all within milliseconds.

The research finding was published Wednesday May 3 in an open-access paper in the Journal of Neural Engineering.

A deep learning-based artificial vision and grasp system

Biomedical engineers at Newcastle University and associates developed a convolutional neural network (CNN), trained it with images of more than 500 graspable objects, and taught it to recognize the grip needed for different types of objects.

Object recognition (top) vs. grasp recognition (bottom) (credit: Ghazal Ghazaei/Journal of Neural Engineering)

Grouping objects by size, shape and orientation, according to the type of grasp that would be needed to pick them up, the team programmed the hand to perform four different grasps: palm wrist neutral (such as when you pick up a cup); palm wrist pronated (such as picking up the TV remote); tripod (thumb and two fingers), and pinch (thumb and first finger).

“We would show the computer a picture of, for example, a stick,” explains lead author Ghazal Ghazae. “But not just one picture; many images of the same stick from different angles and orientations, even in different light and against different backgrounds, and eventually the computer learns what grasp it needs to pick that stick up.”

A block diagram representation of the method (credit: Ghazal Ghazaei/Journal of Neural Engineering)

Current prosthetic hands are controlled directly via the user’s myoelectric signals (electrical activity of the muscles recorded from the skin surface of the stump). That takes learning, practice, concentration and, crucially, time.

A small number of amputees have already trialed the new technology. After training, subjects successfully picked up and moved the target objects with an overall success of up to 88%. Now the Newcastle University team is working with experts at Newcastle upon Tyne Hospitals NHS Foundation Trust to offer the “hands with eyes” to patients at Newcastle’s Freeman Hospital.

A future bionic hand

The work is part of a larger research project to develop a bionic hand that can sense pressure and temperature and transmit the information back to the brain.

Led by Newcastle University and involving experts from the universities of Leeds, Essex, Keele, Southampton and Imperial College London, the aim is to develop novel electronic devices that connect neural networks to the forearm to allow two-way communications with the brain.

The research is funded by the Engineering and Physical Sciences Research Council (EPSRC).


Abstract of Deep learning-based artificial vision for grasp classification in myoelectric hands

Objective. Computer vision-based assistive technology solutions can revolutionise the quality of care for people with sensorimotor disorders. The goal of this work was to enable trans-radial amputees to use a simple, yet efficient, computer vision system to grasp and move common household objects with a two-channel myoelectric prosthetic hand. Approach. We developed a deep learning-based artificial vision system to augment the grasp functionality of a commercial prosthesis. Our main conceptual novelty is that we classify objects with regards to the grasp pattern without explicitly identifying them or measuring their dimensions. A convolutional neural network (CNN) structure was trained with images of over 500 graspable objects. For each object, 72 images, at ${{5}^{\circ}}$ intervals, were available. Objects were categorised into four grasp classes, namely: pinch, tripod, palmar wrist neutral and palmar wrist pronated. The CNN setting was first tuned and tested offline and then in realtime with objects or object views that were not included in the training set. Main results. The classification accuracy in the offline tests reached $85 \% $ for the seen and $75 \% $ for the novel objects; reflecting the generalisability of grasp classification. We then implemented the proposed framework in realtime on a standard laptop computer and achieved an overall score of $84 \% $ in classifying a set of novel as well as seen but randomly-rotated objects. Finally, the system was tested with two trans-radial amputee volunteers controlling an i-limb UltraTM prosthetic hand and a motion controlTM prosthetic wrist; augmented with a webcam. After training, subjects successfully picked up and moved the target objects with an overall success of up to $88 \% $ . In addition, we show that with training, subjects’ performance improved in terms of time required to accomplish a block of 24 trials despite a decreasing level of visual feedback. Significance. The proposed design constitutes a substantial conceptual improvement for the control of multi-functional prosthetic hands. We show for the first time that deep-learning based computer vision systems can enhance the grip functionality of myoelectric hands considerably.

 

Robotic system can 3-D print basic structure of an entire building

Architectural-scale dome section case study for 3-D printing system (top view). For initial tests, the system fabricated the foam-insulation framework used to form a finished concrete structure. As a proof of concept, the researchers used a prototype to build the basic structure of the walls of a 50-foot-diameter, 12-foot-high dome — a project that was completed in less than 14 hours of “printing” time. (credit: Steven Keating, Julian Leland, Levi Cai, and Neri Oxman/Mediated Matter Group)

MIT researchers have designed a “Digital Construction Platform” system that can 3-D print the basic structure of an entire building. It could enable faster, cheaper, more adaptable building construction — replacing traditional fabrication technologies that are dangerous, slow, and energy-intensive in the annual $8.5 trillion construction industry.

The Digital Construction Platform system consists of a tracked vehicle that carries a large, industrial robotic arm, which has a smaller, precision-motion robotic arm (orange) at its end. This highly controllable arm can be used to direct any conventional (or unconventional) construction nozzle, such as those used for pouring concrete or spraying insulation material. The nozzles can be adapted to vary the density of the material being poured, and even to mix different materials as it goes along. The system is equipped with a scoop that could be used to both prepare the building surface and acquire local materials, such as dirt for a rammed-earth building, for the construction itself. The whole system could be operated electrically, even powered by solar panels, as shown here. The system can also create complex shapes and overhangs, which the team demonstrated by including a wide, built-in bench in their prototype dome. (credit: Steven J. Keating et al./Science Robotics)

Described in an open-access paper in the journal Science Robotics, this free-moving system is intended to be self-sufficient and can construct an object of almost any size. It could enable the design and construction of new kinds of buildings that would not be feasible with traditional building methods.

A building could be completely customized to the needs of a particular site and the desires of its maker. Even the internal structure could be modified in new ways — different materials could be incorporated as the process goes along, and material density could be varied to provide optimum combinations of strength, insulation, or other properties.

Rendering showing use of the Digital Construction Platform in an urban environment, including robotic chain welding fabrication — a building as an organism, computationally grown, additively manufactured, and possibly biologically augmented. In the future, the supporting pillars of such a building could be placed in optimal locations based on ground-penetrating radar analysis of the site, and walls could have varying thickness depending on their orientation. For example, a building could have thicker, more insulated walls on its north side in cold climates, or walls that taper from bottom to top as their load-bearing requirements decrease, or curves that help the structure withstand winds. (credit: Steven J. Keating et al./Science Robotics)

The researchers showed that the system can be easily adapted to existing building sites and equipment, and that it will fit existing building codes without requiring whole new evaluations. Such systems could be deployed to remote regions, for example in the developing world, or to areas for disaster relief after a major storm or earthquake, to provide durable shelter rapidly.

Keating says the team’s analysis shows that such construction methods could produce a structure faster and less expensively than present methods can, and would also be much safer by reducing hands-on work*. In addition, because shapes and thicknesses can be optimized for what is needed structurally, rather than having to match what’s available in premade lumber and other materials, the total amount of material needed could be reduced.

For initial tests, the system fabricated a foam-insulation framework. In this construction method, polyurethane foam molds are filled with concrete, similar to traditional commercial insulated-concrete formwork techniques. Any needed wiring and plumbing can be inserted into the mold before the concrete is poured, providing a finished wall structure all at once. It can even incorporate data about the site collected during the process, using built-in sensors for temperature, light, and other parameters to make adjustments to the structure as it is built. (credit: Steven J. Keating et al./Science Robotics)

The ultimate vision is “in the future, to have something totally autonomous, that you could send to the moon or Mars or Antarctica, and it would just go out and make these buildings for years,” says Keating, who led the development of the system as his doctoral thesis work. Meanwhile, “with this process, we can replace one of the key parts of making a building, right now,” he says.

Automated ice structure fabrication in polar environment with power sourced through rollable photovoltaic panels and materials gathered locally. (credit: Steven J. Keating et al./Science Robotics)

Fabrication with local sand to create fractal structures for future immersion in the ocean to support coral reef regrowth. Power sourced via deployable rollable photovoltaics. (credit: Steven J. Keating et al./Science Robotics)

* The International Labour Organization estimated in 2005 that more than 50,000 people die globally in the construction industry per year, accounting for 17% of workplace accident fatalities.


Abstract of Toward site-specific and self-sufficient robotic fabrication on architectural scales

Contemporary construction techniques are slow, labor-intensive, dangerous, expensive, and constrained to primarily rectilinear forms, often resulting in homogenous structures built using materials sourced from centralized factories. To begin to address these issues, we present the Digital Construction Platform (DCP), an automated construction system capable of customized on-site fabrication of architectural-scale structures using real-time environmental data for process control. The system consists of a compound arm system composed of hydraulic and electric robotic arms carried on a tracked mobile platform. An additive manufacturing technique for constructing insulated formwork with gradient properties from dynamic mixing was developed and implemented with the DCP. As a case study, a 14.6-m-diameter, 3.7-m-tall open dome formwork structure was successfully additively manufactured on site with a fabrication time under 13.5 hours. The DCP system was characterized and evaluated in comparison with traditional construction techniques and existing large-scale digital construction research projects. Benefits in safety, quality, customization, speed, cost, and functionality were identified and reported upon. Early exploratory steps toward self-sufficiency—including photovoltaic charging and the sourcing and use of local materials—are discussed along with proposed future applications for autonomous construction.

AI will upload and access our memories, predicts Siri co-inventor

“Hey Siri, what’s the name of that person I met yesterday?” (credit: Apple Inc.)

Instead of replacing humans with robots, artificial intelligence should be used more for augmenting human memory and other human weaknesses, Apple Inc. executive Tom Gruber suggested at the TED 2017 conference yesterday (April 25, 2017).

Thanks to the internet and our smartphones, much of our  personal data is already being captured, notes Gruber, who was one the inventors of voice-controlled intelligent-assistant Siri. Future AI memory enhancement could be especially life-changing for those with Alzheimer’s or dementia, he suggested.

Limitless

“Superintelligence should give us super-human abilities,” he said. “As machines get smarter, so do we. Artificial intelligence can enable partnerships where each human on the team is doing what they do best. Instead of asking how smart we can make our machines, let’s ask how smart our machines can make us.

“I can’t say when or what form factors are involved, but I think it is inevitable,” he said. “What if you could have a memory that was as good as computer memory and is about your life? What if you could remember every person you ever met? How to pronounce their name? Their family details? Their favorite sports? The last conversation you had with them?”

Gruber’s ideas mesh with a prediction by Ray Kurzweil: “Once we have achieved complete models of human intelligence, machines will be capable of combining the flexible, subtle human levels of pattern recognition with the natural advantages of machine intelligence, in speed, memory capacity, and, most importantly, the ability to quickly share knowledge and skills.”

Two projects announced last week aim in that direction: Facebook’s plan to develop a non-invasive brain-computer interface that will let you type at 100 words per minute and Elon Musks’ proposal that we become superhuman cyborgs to deal with superintelligent AI.

But trusting machines also raises security concerns, Gruber warned. “We get to choose what is and is not recalled,” he said. “It’s absolutely essential that this be kept very secure.”

 

 

 

 

Elon Musk wants to enhance us as superhuman cyborgs to deal with superintelligent AI

(credit: Neuralink Corp.)

It’s the year 2021. A quadriplegic patient has just had one million “neural lace” microparticles injected into her brain, the world’s first human with an internet communication system using a wireless implanted brain-mind interface — and empowering her as the first superhuman cyborg. …

No, this is not a science-fiction movie plot. It’s the actual first public step — just four years from now — in Tesla CEO Elon Musk’s business plan for his latest new venture, Neuralink. It’s now explained for the first time on Tim Urban’s WaitButWhy blog.

Dealing with the superintelligence existential risk

Such a system would allow for radically improved communication between people, Musk believes. But for Musk, the big concern is AI safety. “AI is obviously going to surpass human intelligence by a lot,” he says. “There’s some risk at that point that something bad happens, something that we can’t control, that humanity can’t control after that point — either a small group of people monopolize AI power, or the AI goes rogue, or something like that.”

“This is what keeps Elon up at night,” says Urban. “He sees it as only a matter of time before superintelligent AI rises up on this planet — and when that happens, he believes that it’s critical that we don’t end up as part of ‘everyone else.’ That’s why, in a future world made up of AI and everyone else, he thinks we have only one good option: To be AI.”

Neural dust: an ultrasonic, low power solution for chronic brain-machine interfaces (credit: Swarm Lab/UC Berkeley)

To achieve his, Neuralink CEO Musk has met with more than 1,000 people, narrowing it down initially to eight experts, such as Paul Merolla, who spent the last seven years as the lead chip designer at IBM on their DARPA-funded SyNAPSE program to design neuromorphic (brain-inspired) chips with 5.4 billion transistors (each with 1 million neurons and 256 million synapses), and Dongjin (DJ) Seo, who while at UC Berkeley designed an ultrasonic backscatter system for powering and communicating with implanted bioelectronics called neural dust for recording brain activity.*

Mesh electronics being injected through sub-100 micrometer inner diameter glass needle into aqueous solution (credit: Lieber Research Group, Harvard University)

Becoming one with AI — a good thing?

Neuralink’s goal its to create a “digital tertiary layer” to augment the brain’s current cortex and limbic layers — a radical high-bandwidth, long-lasting, biocompatible, bidirectional communicative, non-invasively implanted system made up of micron-size (millionth of a meter) particles communicating wirelessly via the cloud and internet to achieve super-fast communication speed and increased bandwidth (carrying more information).

“We’re going to have the choice of either being left behind and being effectively useless or like a pet — you know, like a house cat or something — or eventually figuring out some way to be symbiotic and merge with AI. … A house cat’s a good outcome, by the way.”

Thin, flexible electrodes mounted on top of a biodegradable silk substrate could provide a better brain-machine interface, as shown in this model. (credit: University of Illinois at Urbana-Champaign)

But machine intelligence is already vastly superior to human intelligence in specific areas (such as Google’s Alpha Go) and often inexplicable. So how do we know superintelligence has the best interests of humanity in mind?

“Just an engineering problem”

Musk’s answer: “If we achieve tight symbiosis, the AI wouldn’t be ‘other’  — it would be you and with a relationship to your cortex analogous to the relationship your cortex has with your limbic system.” OK, but then how does an inferior intelligence know when it’s achieved full symbiosis with a superior one — or when AI goes rogue?

Brain-to-brain (B2B) internet communication system: EEG signals representing two words were encoded into binary strings (left) by the sender (emitter) and sent via the internet to a receiver. The signal was then encoded as a series of transcranial magnetic stimulation-generated phosphenes detected by the visual occipital cortex, which the receiver then translated to words (credit: Carles Grau et al./PLoS ONE)

And what about experts in neuroethics, psychology, law? Musk says it’s just “an engineering problem. … If we can just use engineering to get neurons to talk to computers, we’ll have done our job, and machine learning can do much of the rest.”

However, it’s not clear how we could be assured our brains aren’t hacked, spied on, and controlled by a repressive government or by other humans — especially those with a more recently updated software version or covert cyborg hardware improvements.

NIRS/EEG brain-computer interface system using non-invasive near-infrared light for sensing “yes” or “no” thoughts, shown on a model (credit: Wyss Center for Bio and Neuroengineering)

In addition, the devices mentioned in WaitButWhy all require some form of neurosurgery, unlike Facebook’s research project to use non-invasive near-infrared light, as shown in this experiment, for example.** And getting implants for non-medical use approved by the FDA will be a challenge, to grossly understate it.

“I think we are about 8 to 10 years away from this being usable by people with no disability,” says Musk, optimistically. However, Musk does not lay out a technology roadmap for going further, as MIT Technology Review notes.

Nonetheless, Neuralink sounds awesome — it should lead to some exciting neuroscience breakthroughs. And Neuralink now has 16 San Francisco job listings here.

* Other experts: Vanessa Tolosa, Lawrence Livermore National Laboratory, one of the world’s foremost researchers on biocompatible materials; Max Hodak, who worked on the development of some groundbreaking BMI technology at Miguel Nicolelis’s lab at Duke University, Ben Rapoport, Neuralink’s neurosurgery expert, with a Ph.D. in Electrical Engineering and Computer Science from MIT; Tim Hanson, UC Berkeley post-doc and expert in flexible Electrodes for Stable, Minimally-Invasive Neural Recording; Flip Sabes, professor, UCSF School of Medicine expert in cortical physiology, computational and theoretical modeling, and human psychophysics and physiology; and Tim Gardner, Associate Professor of Biology at Boston University, whose lab works on implanting BMIs in birds, to study “how complex songs are assembled from elementary neural units” and learn about “the relationships between patterns of neural activity on different time scales.”

** This binary experiment and the binary Brain-to-brain (B2B) internet communication system mentioned above are the equivalents of the first binary (dot–dash) telegraph message, sent May 24, 1844: ”What hath God wrought?”

Carnegie Mellon University AI beats top Chinese poker players

Carnegie Mellon University professor Tuomas Sandholm talks to Kai-Fu Lee, head of Sinovation Ventures, a Chinese venture capital firm, as Lee plays poker against Lengpudashi AI (credit: Sinovation Ventures)

Artificial intelligence (AI) triumphed over human poker players again (see “Carnegie Mellon AI beats top poker pros — a first“), as a computer program developed by Carnegie Mellon University (CMU) researchers beat six Chinese players by a total of $792,327 in virtual chips during a five-day, 36,000-hand exhibition that ended today (April 10, 2017) in Hainan, China.

The AI software program, called Lengpudashi (“cold poker master”) is a version of Libratus, the CMU AI that beat four top poker professionals during a 20-day, 120,000-hand Heads-Up No-Limit Texas Hold’em competition in January in Pittsburgh, Pennsylvania.

Strategic Machine Inc.*, a company founded by Tuomas Sandholm, professor of computer science and co-creator of Libratus/Lengpudashi with Noam Brown, a Ph.D. student in computer science, will take home a pot worth approximately $290,000.

Results of the tournament pitting Lengpudashi AI against four top poker professionals (credit: Sinovation Ventures)

The human players, called Team Dragons, were led by Alan Du, a Shanghai venture capitalist who won a 2016 World Series of Poker bracelet.

The exhibition was organized by Kai-Fu Lee, a CMU alumnus and former faculty member who is CEO of Sinovation Ventures, an early-stage venture capital firm that invests in startups in China and the United States. He is a former executive of Apple, Microsoft and Google, and is one of the most prominent figures in China’s internet sector.

* Strategic Machine has exclusively licensed Libratus and other technologies from Sandholm’s CMU laboratory. Strategic Machine targets a broad set of applications: poker and other recreational games, business strategy, negotiation, cybersecurity, physical security, military applications, strategic pricing, finance, auctions, political campaigns, and medical treatment planning.

Alpha Go to take on world’s number one Go player in China

The world’s number one Go player, Ke Jie (far right) and associates have recreated the opening moves of one of AlphaGo’s games with Lee Sedol from memory to explain the beauty of its moves to Google CEO Sundar Pichai (second from left) during a visit Pichai made to Nie Weiping’s Go school in Beijing last year (credit: DeepMind)

DeepMind’s Alpha Go AI software will take on China’s top Go players in “The Future of Go Summit” — a five-day festival of Go and artificial intelligence in the game’s birthplace, China, on May 23–27, DeepMind Co-Founder & CEO Demis Hassabis announced today (April 10, 2017).

The summit will feature a variety of game formats involving AlphaGo and top Chinese players, specifically designed to explore the mysteries of the game together, but “the centerpiece of the event will be a classic 1:1 match of three games between AlphaGo and the world’s number one player, Ke Jie, to push AlphaGo to its limits,” Hassabis said.

The festival will also include a forum on the “Future of A.I.” in which leading experts from Google and China will explore “how AlphaGo has created new knowledge about the oldest of games, and how the technologies behind AlphaGo, machine learning, and artificial intelligence are bringing solutions to some of the world’s greatest challenges into reach.”

In January 2016, the AlphaGo deep learning computer system was the first computer program to defeat a Go champion, Korean Lee Sudow, shocking many observers of the game and marking a major breakthrough for AI.

DeepMind was founded in London in 2010 and backed by successful tech entrepreneurs. Having been acquired by Google in 2014, it is now part of the Alphabet group.