Artificial intelligence marketing (AIM) is a form of direct marketing leveraging database marketing techniques as well as AI concept and model such as machine learning and Bayesian Network. The main difference resides in the reasoning part which suggests it is performed by computer and algorithm instead of human
Ignore today’s small incremental advancements in artificial intelligence, such as the enhancing capabilities of automobiles to drive themselves. Waiting in the wings could be a groundbreaking growth: a machine that knows itself as well as its environments, which might take in and also procedure huge amounts of data in real time. It could be sent on harmful goals, right into room or fight. Along with driving people about, it might be able to prepare, tidy, do washing– as well as keep people company when other people typically aren’t close by.
A specifically innovative set of machines might replace people at essentially all jobs. That would save humankind from workaday grind, yet it would certainly likewise tremble several societal foundations. A life of no job and also only play might turn out to be a dystopia.
Mindful equipments would additionally elevate troubling lawful as well as honest troubles. Would certainly a mindful machine be a “person” under regulation as well as be responsible if its actions hurt someone, or if something goes wrong? To consider an extra frightening circumstance, might these machines rebel against human beings and also desire to eliminate us completely? If yes, they represent the culmination of advancement.
As a teacher of electric design and computer science that operates in artificial intelligence and also quantum theory, I can state that scientists are split on whether these type of hyperaware machines will certainly ever before exist. There’s additionally dispute regarding whether machines might or ought to be called “aware” in the method we think about human beings, as well as some pets, as aware. A few of the questions pertain to innovation; others relate to what consciousness in fact is.
Is Recognition Sufficient? Many computer researchers assume that awareness is a particular that will certainly emerge as innovation develops. Some believe that awareness includes approving brand-new information, saving as well as fetching old info and cognitive processing of all of it right into assumptions and activities. If that’s right, then one day makers will certainly undoubtedly be the best consciousness. They’ll be able to collect even more information than a human, shop more than numerous collections, accessibility substantial databases in milliseconds and also calculate all of it right into decisions extra complex, and yet a lot more sensible, than any person ever before could.
On the various other hand, there are physicists and also thinkers who claim there’s something more regarding human habits that can not be calculated by a maker. Creative thinking, for example, and also the sense of freedom individuals possess don’t show up ahead from logic or calculations.
Yet these are not the only sights of what consciousness is, or whether devices could ever before accomplish it.
Quantum Views One more perspective on awareness comes from quantum theory, which is the inmost theory of physics. Inning accordance with the orthodox Copenhagen Analysis, awareness as well as the real world are corresponding aspects of the very same fact. When a person observes, or experiments on, some aspect of the physical world, that individual’s conscious interaction causes noticeable change. Considering that it takes consciousness as a given as well as no effort is made to derive it from physics, the Copenhagen Analysis may be called the “big-C” view of consciousness, where it is a thing that exists on its own– although it needs brains to come to be real. This view was prominent with the pioneers of quantum concept such as Niels Bohr, Werner Heisenberg and Erwin Schrodinger.
The communication in between consciousness and also issue leads to paradoxes that remain unsolved after 80 years of argument. A widely known example of this is the mystery of Schrodinger’s cat, where a pet cat is placed in a scenario that results in it being similarly likely to endure or pass away– and the act of monitoring itself is what makes the end result certain.
The opposing view is that awareness emerges from biology, just as biology itself emerges from chemistry which, consequently, emerges from physics. We call this less extensive concept of consciousness “little-C.” It concurs with the neuroscientists’ sight that the processes of the mind correspond states and processes of the brain. It also agrees with a more recent analysis of quantum theory encouraged by an effort to clear it of mysteries, the Several Worlds Interpretation, where observers belong of the mathematics of physics.
Theorists of science believe that these modern-day quantum physics sights of consciousness have parallels in old philosophy. Big-C resembles the theory of mind in Vedanta– in which consciousness is the essential basis of truth, on the same level with the physical world.
Little-C, on the other hand, is fairly much like Buddhism. Although the Buddha chose not to address the inquiry of the nature of awareness, his fans stated that mind and also consciousness arise out of emptiness or nothingness.
Big-C and Scientific Exploration Researchers are additionally exploring whether awareness is constantly a computational process. Some scholars have actually suggested that the imaginative moment is not at the end of a calculated computation. For example, fantasizes or visions are intended to have influenced Elias Howe’s 1845 style of the contemporary embroidery device, as well as August Kekule’s exploration of the framework of benzene in 1862.
A dramatic item of proof in favor of big-C consciousness existing all on its own is the life of self-taught Indian mathematician Srinivasa Ramanujan, who died in 1920 at the age of 32. His note pad, which was lost as well as neglected for regarding 50 years and published just in 1988, contains a number of thousand formulas, without evidence in various areas of mathematics, that were well ahead of their time. Moreover, the methods whereby he located the solutions remain elusive. He himself declared that they were revealed to him by a siren while he was asleep.
The principle of big-C consciousness increases the inquiries of exactly how it relates to matter, as well as how matter and also mind mutually affect each other. Awareness alone can not make physical modifications to the world, yet maybe it could change the probabilities in the advancement of quantum procedures. The act of monitoring can freeze and even affect atoms’ motions, as Cornell physicists verified in 2015. This might quite possibly be an explanation of exactly how matter and mind engage.
Mind and Self-Organizing Solutions It is feasible that the sensation of consciousness calls for a self-organizing system, like the brain’s physical framework. If so, then present makers will come up short.
Scholars aren’t sure if adaptive self-organizing equipments could be designed to be as advanced as the human mind; we lack a mathematical theory of calculation for systems like that. Probably it holds true that just biological machines could be sufficiently imaginative and adaptable. However then that recommends individuals ought to– or quickly will certainly– begin working on engineering brand-new biological frameworks that are, or could end up being, mindful.
I was asked the question by the head of a new startup for AI as their technology aims to change the world I quote. Will jobs done by regular people be replaced? Fast Company predicts these will be the jobs that will be the worst hit. 1. INSURANCE UNDERWRITERS AND CLAIMS REPRESENTATIVES 2. BANK TELLERS […]
Artificial intelligence (AI, also machine intelligence, MI) is intelligence exhibited by machines, rather than humans or other animals (natural intelligence, NI). In computer science, the field of AI research defines itself as the study of “intelligent agents”: any device that perceives its environment and takes actions that maximize its chance of success at some goal. Colloquially, the term “artificial intelligence” is applied when a machine mimics “cognitive” functions that humans associate with other human minds, such as “learning” and “problem solving”.
The scope of AI is disputed: as machines become increasingly capable, tasks considered as requiring “intelligence” are often removed from the definition, a phenomenon known as the AI effect, leading to the quip “AI is whatever hasn’t been done yet.” For instance, optical character recognition is frequently excluded from “artificial intelligence”, having become a routine technology. Capabilities generally classified as AI, as of 2017, include successfully understanding human speech, competing at a high level in strategic game systems (such as chess and Go), autonomous cars, intelligent routing in content delivery networks, military simulations, and interpreting complex data.
Artificial intelligence was founded as an academic discipline in 1956, and in the years since has experienced several waves of optimism, followed by disappointment and the loss of funding (known as an “AI winter”), followed by new approaches, success and renewed funding. For most of its history, AI research has been divided into subfields that often fail to communicate with each other. However, in the early 21st century statistical approaches to machine learning became successful enough to eclipse all other tools, approaches, problems and schools of thought.
The traditional problems (or goals) of AI research include reasoning, knowledge, planning, learning, natural language processing, perception and the ability to move and manipulate objects. General intelligence is among the field’s long-term goals. Approaches include statistical methods, computational intelligence, and traditional symbolic AI. Many tools are used in AI, including versions of search and mathematical optimization, neural networks and methods based on statistics, probability and economics. The AI field draws upon computer science, mathematics, psychology, linguistics, philosophy, neuroscience, artificial psychology and many others.
The field was founded on the claim that human intelligence “can be so precisely described that a machine can be made to simulate it”. This raises philosophical arguments about the nature of the mind and the ethics of creating artificial beings endowed with human-like intelligence, issues which have been explored by myth, fiction and philosophy since antiquity. Some people also consider AI a danger to humanity if it progresses unabatedly.
In the twenty-first century, AI techniques have experienced a resurgence following concurrent advances in computer power, large amounts of data, and theoretical understanding, and AI techniques have become an essential part of the technology industry, helping to solve many challenging problems in computer science.
I used to have a description of each of my papers on this page, but it got very boring to read as the numbers grew, so I moved most of it to here. After graduate work on the role of atomic and molecular chemistry in cosmic reionization, I have mainly focused my research on issues related to constraining cosmological models. A suite of papers developed methods for analyzing cosmological data sets and applied them to various CMB experiments and galaxy redshift surveys, often in collaboration with the experimentalists who had taken the data. Another series of papers tackled various “dirty laundry” issues such as microwave foregrounds and mass-to-light bias. Other papers like this one develop and apply techniques for clarifying the big picture in cosmology: comparing and combining diverse cosmological probes, cross-checking for consistency and constraining cosmological models and their free parameters. (The difference between cosmology and ice hockey is that I don’t get penalized for cross-checking…) My main current research interest is cosmology theory and phenomenology. I’m particularly enthusiastic about the prospects of comparing and combining current and upcoming data on CMB, LSS, galaxy clusters, lensing, LyA forest clustering, SN 1, 21 cm tomography, etc. to raise the ambition level beyond the current cosmological parameter game, testing rather than assuming the underlying physics. This paper contains my battle cry. I also retain a strong interest in low-level nuts-and-bolts analysis and interpretation of data, firmly believing that the devil is in the details, and am actively working on neutral hydrogen tomography theory, experiment and data analysis for our Omniscope project, which you can read all about here.
OTHER RESEARCH: SIDE INTERESTS Early galaxy formation and the end of the cosmic dark ages One of the main challenges in modern cosmology is to quantify how small density fluctuations at the recombination epoch at redshift around z=1000 evolved into the galaxies and the large-scale structure we observe in the universe today. My Ph.D. thesis with Joe Silk focused on ways of probing the interesting intermediate epoch. The emphasis was on the role played by non-linear feedback, where a small fraction of matter forming luminous objects such as stars or QSO’s can inject enough energy into their surrounding to radically alter subsequent events. We know that the intergalactic medium (IGM) was reionized at some point, but the details of when and how this occurred remain open. The absence of a Gunn-Peterson trough in the spectra of high-redshift quasars suggests that it happened before z=5, which could be achieved through supernova driven winds from early galaxies. Photoionization was thought to be able to partially reionize the IGM much earlier, perhaps early enough to affect the cosmic microwave background (CMB) fluctuations, especially in an open universe. However, extremely early reionization is ruled out by the COBE FIRAS constraints on the Compton y-distortion. To make predictions for when the first objects formed and how big they were, you need to worry about something I hate: molecules. Although I was so fed up with rate discrepancies in the molecule literature that I verged on making myself a Ghostbuster-style T-shirt reading “MOLECULES – JUST SAY NO”, the irony is that my molecule paper that I hated so much ended up being one of my most cited ones. Whereas others that I had lots of fun with went largely unnoticed…
Math problemsI’m also interested in physics-related mathematics problems in general. For instance, if you don’t believe that part of a constrained elliptic metal sheet may bend towards you if you try to push it away, you are making the same mistake that the famous mathematician Hadamard once did.
WELCOME TO MY TECHNICAL UNIVERSE I love working on projects that involve cool questions, great state-of-the-art data and powerful physical/mathematical/computational tools. During my first quarter-century as a physics researcher, this criterion has lead me to work mainly on cosmology and quantum information. Although I’m continuing my cosmology work with the HERA collaboration, the main focus of my current research is on the physics of cognitive systems: using physics-based techniques to understand how brains works and to build better AI (artificial intelligence) systems. If you’re interested in working with me on these topics, please let me know, as I’m potentially looking for new students and postdocs (see requirements). I’m fortunate to have collaborators who generously share amazing neuroscience data with my group, including Ed Boyden, Emery Brown and Tomaso Poggio at MIT and Gabriel Kreimann at Harvard, and to have such inspiring colleagues here in our MIT Physics Department in our new division studying the physics of living systems. I’ve been pleasantly surprised by how many data analysis techniques I’ve developed for cosmology can be adapted to neuroscience data as well. There’s clearly no shortage of fascinating questions surrounding the physics of intelligence, and there’s no shortage of powerful theoretical tools either, ranging from neural network physics and non-equilibrium statistical mechanics to information theory, the renormalization group and deep learning. Intriguingly and surprisingly, there’s a duality between the last two. I recently helped organize conferences on the physics of information and artificial intelligence. I’m very interested in the question of how to model an observer in physics, and if simple necessary conditions for a physical system being a conscious observer can help explain how the familiar object hierarchy of the classical world emerges from the raw mathematical formalism of quantum mechanics. Here’s a taxonomy of proposed consciousness measures. Here’s a TEDx-talk of mine about the physics of consciousness. Here’s an intriguing connection between critical behavior in magnets, language, music and DNA. In older work of mine on the physics of the brain, I showed that neuron decoherence is way too fast for the brain to be a quantum computer. However, it’s nonetheless interesting to study our brains as quantum systems, to better understand why they perceives the sort of classical world that they do. For example, why do we feel that we live in real space rather than Fourier space, even though both are equally valid quantum descriptions related by a unitary transformation?
Quantum information My work on the physics of cognitive systems is a natural outgrowth of my long-standing interest in quantum information, both for enabling new technologies such as quantum computing and for shedding new light on how the world fundamentally works. For example, I’m interested in how the second law of thermodynamics can be generalized to explain how the entropy of a system typically decreases while you observe a system and increases while you don’t, and how this can help explain how inflation causes the emergence of an arrow of time. When you don’t observe an interacting system, you can get decoherence, which I had the joy of rediscovering as a grad student – if you’d like to know more about what this is, check out my article in with John Archibald Wheeler in Scientific American here. I’m interested in decoherence both for its quantitative implications for quantum computing etc and for its philosophical implications for the interpretation of quantum mechanics. For much more on this wackier side of mine, click the banana icon above. Since macroscopic systems are virtually impossible to isolate from their surroundings, a number of quantitative predictions can be made for how their wavefunction will appear to collapse, in good agreement with what we in fact observe. Similar quantitative predictions can be made for models of heat baths, showing how the effects of the environment cause the familiar entropy increase and apparent directionality of time. Intriguingly, decoherence can also be shown to produce generalized coherent states, indicating that these are not merely a useful approximation, but indeed a type of quantum states that we should expect nature to be full of. All these changes in the quantum density matrix can in principle be measured experimentally, with phases and all.
Cosmology My cosmology research has been focused on precision cosmology, e.g., combining theoretical work with new measurements to place sharp constraints on cosmological models and their free parameters. (Skip to here if you already know all this.) Spectacular new measurements are providing powerful tools for this:
So far, I’ve worked mainly on CMB, LSS and 21 cm tomography, with some papers involving lensing, SN Ia and LyAF as well. Why do I find cosmology exciting?(Even if you don’t find cosmology exciting, there are good reasons why you should support physics research.)
There are some very basic questions that still haven’t been answered. For instance,
Is really only 5% of our universe made of atoms? So it seems, but what precisely is the weird “dark matter” and “dark energy” that make up the rest?
Will the Universe expand forever or end in a cataclysmic crunch or big rip? The smart money is now on the first option, but the jury is still out.
How did it all begin, or did it? This is linked to particle physics and unifying gravity with quantum theory.
Are there infinitely many other stars, or does space connect back on itself? Most of my colleagues assume it is infinite and the data supports this, but we don’t know yet.
Thanks to an avalanche of great new data, driven by advances in satellite, detector and computer technology, we may be only years away from answering some of these questions.
Since our atmosphere messes up most electromagnetic waves coming from space (the main exceptions being radio waves and visible light), the advent of satellites has revolutionized our ability to photograph the Universe in microwaves, infrared light, ultraviolet light, X-rays and gamma rays. New low-temperature detectors have greatly improved what can be done from the ground as well, and the the computer revolution has enabled us to gather and process huge data quantities, doing research that would have been unthinkable twenty years ago. This data avalanche has transformed cosmology from being a mainly theoretical field, occasionally ridiculed as speculative and flaky, into a data-driven quantitative field where competing theories can be tested with ever-increasing precision. I find CMB, LSS, lensing, SN Ia, LyAF, clusters and BBN to be very exciting areas, since they are all being transformed by new high-precision measurements as described below. Since each of them measures different but related aspects of the Universe, they both complement each other and allow lots of cross-checks. What are these cosmological parameters? In our standard cosmological model, the Universe was once in an extremely dense and hot state, where things were essentially the same everywhere in space, with only tiny fluctuations (at the level of 0.00001) in the density. As the Universe expanded and cooled, gravitational instability caused these these fluctuations to grow into the galaxies and the large-scale structure that we observe in the Universe today. To calculate the details of this, we need to know about a dozen numbers, so-called cosmological parameters. Most of these parameters specify the cosmic matter budget, i.e., what the density of the Universe is made up of – the amounts of the following ingredients:
Baryons – the kind of particles that you and I and all the chemical elements we learned about in school are madeof : protons & neutrons. Baryons appear to make up only about 5% of all stuff in the Universe.
Photons – the particles that make uplight. Their density is the best measured one on this list.
Massive neutrinos – neutrinos are very shy particles. They are known to exist, and now at least two of the three or more kinds are known to have mass.
Cold dark matter – unseen mystery particles widely believed to exist. There seems to be about five times more of this strange stuff than baryons, making us a minority in the Universe.
Curvature – if the total density differs from a certain critical value, space will be curved. Sufficiently high density would make space be finite, curving back on itself like the 3D surface of a 4D hypersphere.
Dark energy – little more than a fancy name our ignorance of what seems to make up abouttwo thirdsof the matter budget. One popular candidates is a “Cosmological constant”, a.k.a. Lambda, which Einstein invented and then later called his greatest blunder. Other candidates are more complicated modifications toEinsteinstheory of Gravity as well as energy fields known as “quintessence”. Dark energy causes gravitational repulsion in place of attraction. Einstein invented it and called it his greatest mistake, but combining new SN Ia and CMB data indicates that we might be living with Lambda after all.
Then there are a few parameters describing those tiny fluctuations in the early Universe; exactly how tiny they were, the ratio of fluctuations on small and large scales, the relative phase of fluctuations in the different types of matter, etc. Accurately measuring these parameters would test the most popular theory for the origin of these wiggles, known as inflation, and teach us about physics at much higher energies than are accessible with particle accelerator experiments. Finally, there are a some parameters that Dick Bond, would refer to as “gastrophysics”, since they involve gas and other ghastly stuff. One example is the extent to which feedback from the first galaxies have affected the CMB fluctuations via reionization. Another example is bias, the relation between fluctuations in the matter density and the number of galaxies.One of my main current interests is using the avalanche of new data to raise the ambition level beyond cosmological parameters, testing rather than assuming the underlying physics. My battle cry is published here with nuts and bolts details here and here. The cosmic toolboxHere is a brief summary of some key cosmological observables and what they can teach us about cosmological parameters.
Photos of the cosmic microwave background (CMB) radiation like the one to the left show us the most distant object we can see: a hot, opaque wall of glowing hydrogen plasma about 14 billion light years away. Why is it there? Well, as we look further away, we’re seeing things that happened longer ago, since it’s taken the light a long time to get here. We see the Sun as it was eight minutes ago, the Andromeda galaxy the way it was a few million years ago and this glowing surface as it was just 400,000 years after the Big Bang. We can see that far back since the hydrogen gas that fills intergalactic space is transparent, but we can’t see further, since earlier the hydrogen was so hot that it was an ionized plasma, opaque to light, looking like a hot glowing wall just like the surface of the Sun. The detailed patterns of hotter and colder spots on this wall constitute a goldmine of information about the cosmological parameters mentioned above. If you are a newcomer and want an introduction to CMB fluctuations and what we can learn from them, I’ve written a review here. If you don’t have a physics background, I recommend the on-line tutorials by Wayne Hu and Ned Wright. Two new promising CMB fronts are opening up — CMB polarization and arcminute scale CMB, and are likely to keep the CMB field lively for at leastr another decade. Hydrogen tomography Mapping our universe in 3D by imaging the redshifted 21 cm line from neutral hydrogen has the potential to overtake the cosmic microwave background as our most powerful cosmological probe, because it can map a much larger volume of our Universe, shedding new light on the epoch of reionization, inflation, dark matter, dark energy, and neutrino masses. For this reason, my group built MITEoR, a pathfinder low-frequency radio interferometer whose goal was to test technologies that greatly reduce the cost of such 3D mapping for a given sensitivity. MITEoR accomplished this by using massive baseline redundancy both to enable automated precision calibration and to cut the correlator cost scaling from N2 to N log N, where N is the number of antennas. The success of MITEoR with its 64 dual-polarization elements bodes well for the more ambitious HERA project, which incorporates many of the technologies MITEoR tested using dramatically larger collecting area
. Large-scale structure: 3D mapping of the Universe with galaxy redshift surveys offers another window on dark matter properties, through its gravitational effects on galaxy clustering. This field is currently being transformed by everr larger Galaxy Redshift Survey. I’ve had lots of fun working with my colleagues on the Sloan Digital Sky Survey (SDSS) to carefully analyze the gargantuan galaxy maps and work out what they tell us about our cosmic composition, origins and ultimate fate. The abundance of galaxy clusters, the largest gravitationally bound and equilibrated blobs of stuff in the Universe, is a very sensitive probe of both the cosmic expansion history and the growth of matter clustering. Many powerful cluster finding techniques are contributing to rapid growth in the number of known clusters and our knowledge of their properties: identifying them in 3D galaxy surveys, seeing their hot gas as hot spots in X-ray maps or cold spots in microwave maps (the so-called SZ-effect) or spotting their gravitational effects with gravitational lensing. Yet another probe of dark matter is offered by gravitational lensing, whereby its gravitational pull bends light rays and distorts images of distant objects. The first large-scale detections of this effect were reported by four groups (astro-ph/0002500, 0003008, 0003014, 0003338) in the year 2000, and I anticipate making heavy use of such measurements as they continue to improve, partly in collaboration with Bhuvnesh Jain at Penn. Lensing is ultimately as promising as CMB and is free from the murky bias issues plaguing LSS and LyAF measurements, since it probes the matter density directly via its gravitational pull. I’ve also dabbled some in the stronger lensing effects caused by galaxy cores, which offer additional insights into the detailed nature of the dark matter.Supernovae Ia: If a white dwarf (the corpse of a burned-out low-mass star like our Sun) orbits another dying star, it may gradually steal its gas and exceed the maximum mass with which it can be stable. This makes it collapse under its own weight and blow up in a cataclysmic explosion called a supernova of type Ia. Since all of these cosmic bombs weigh the same when they go off (about 1.4 solar masses, the so-called Chandrasekhar mass), they all release roughly the same amount of energy – and a more detailed calibration of this energy is possible by measuring how fast it dims, making it the best “standard candle” visible at cosmological distances. The supernova cosmology project and the high z SN search team mapped out how bright SN Ia looked at different redshifts found the first evidence in 1998 that the expansion of the Universe was accelerating. This approach can ultimately provide a direct measurement of the density of the Universe as a function of time, helping unravel the nature of dark energy – I hope the SNAP project or one of its competitores gets funded. The image to the left resulted from a different type of supernova, but I couldn’t resist showing it anyway..
. The so-called Lyman Alpha Forest, cosmic gas clouds backlit by quasars, offers yet another new and exciting probe of how dark has clumped ordinary matter together, and is sensitive to an epoch when the Universe was merely 10-20% of its present age. Although relating the measured absorption to the densities of gas and dark matter involves some complications, it completely circumvents the Pandora’s of galaxy biasing. Cosmic observations are rapidly advancing on many other fronts as well, e.g., with direct measurements of the cosmic expansion rate and the cosmic baryon fraction.
This month scientists published rare footage of one of the Arctic’s most elusive sharks. The findings demonstrate that, even with many technological advances in recent years, it remains a challenging task to document marine life up close.
But MIT computer scientists believe they have a possible solution: using robots.
In a paper out today, a team from MIT’s Computer Science and Artificial Intelligence Laboratory (CSAIL) unveiled “SoFi,” a soft robotic fish that can independently swim alongside real fish in the ocean.
During test dives in the Rainbow Reef in Fiji, SoFi swam at depths of more than 50 feet for up to 40 minutes at once, nimbly handling currents and taking high-resolution photos and videos using (what else?) a fisheye lens.
Using its undulating tail and a unique ability to control its own buoyancy, SoFi can swim in a straight line, turn, or dive up or down. The team also used a waterproofed Super Nintendo controller and developed a custom acoustic communications system that enabled them to change SoFi’s speed and have it make specific moves and turns.
“To our knowledge, this is the first robotic fish that can swim untethered in three dimensions for extended periods of time,” says CSAIL PhD candidate Robert Katzschmann, lead author of the new journal article published today in ScienceRobotics. “We are excited about the possibility of being able to use a system like this to get closer to marine life than humans can get on their own.”
Katzschmann worked on the project and wrote the paper with CSAIL director Daniela Rus, graduate student Joseph DelPreto and former postdoc Robert MacCurdy, who is now an assistant professor at the University of Colorado at Boulder.
How it works
Existing autonomous underwater vehicles (AUVs) have traditionally been tethered to boats or powered by bulky and expensive propellers.
In contrast, SoFi has a much simpler and more lightweight setup, with a single camera, a motor, and the same lithium polymer battery that’s found in consumer smartphones. To make the robot swim, the motor pumps water into two balloon-like chambers in the fish’s tail that operate like a set of pistons in an engine. As one chamber expands, it bends and flexes to one side; when the actuators push water to the other channel, that one bends and flexes in the other direction.
These alternating actions create a side-to-side motion that mimics the movement of a real fish. By changing its flow patterns, the hydraulic system enables different tail maneuvers that result in a range of swimming speeds, with an average speed of about half a body length per second.
“The authors show a number of technical achievements in fabrication, powering, and water resistance that allow the robot to move underwater without a tether,” says Cecilia Laschi, a professor of biorobotics at the Sant’Anna School of Advanced Studies in Pisa, Italy. “A robot like this can help explore the reef more closely than current robots, both because it can get closer more safely for the reef and because it can be better accepted by the marine species.”
The entire back half of the fish is made of silicone rubber and flexible plastic, and several components are 3-D-printed, including the head, which holds all of the electronics. To reduce the chance of water leaking into the machinery, the team filled the head with a small amount of baby oil, since it’s a fluid that will not compress from pressure changes during dives.
Indeed, one of the team’s biggest challenges was to get SoFi to swim at different depths. The robot has two fins on its side that adjust the pitch of the fish for up and down diving. To adjust its position vertically, the robot has an adjustable weight compartment and a “buoyancy control unit” that can change its density by compressing and decompressing air.
Katzschmann says that the team developed SoFi with the goal of being as nondisruptive as possible in its environment, from the minimal noise of the motor to the ultrasonic emissions of the team’s communications system, which sends commands using wavelengths of 30 to 36 kilohertz.
“The robot is capable of close observations and interactions with marine life and appears to not be disturbing to real fish,” says Rus.
The project is part of a larger body of work at CSAIL focused on soft robots, which have the potential to be safer, sturdier, and more nimble than their hard-bodied counterparts. Soft robots are in many ways easier to control than rigid robots, since researchers don’t have to worry quite as much about having to avoid collisions.
“Collision avoidance often leads to inefficient motion, since the robot has to settle for a collision-free trajectory,” says Rus, the Andrew and Erna Viterbi Professor of Electrical Engineering and Computer Science at MIT. “In contrast, a soft robot is not just more likely to survive a collision, but could use it as information to inform a more efficient motion plan next time around.”
As next steps the team will be working on several improvements on SoFi. Katzschmann plans to increase the fish’s speed by improving the pump system and tweaking the design of its body and tail.
He says that they also plan to soon use the on-board camera to enable SoFi to automatically follow real fish, and to build additional SoFis for biologists to study how fish respond to different changes in their environment.
“We view SoFi as a first step toward developing almost an underwater observatory of sorts,” says Rus. “It has the potential to be a new type of tool for ocean exploration and to open up new avenues for uncovering the mysteries of marine life.”
This project was supported by the National Science Foundation.
Daniel Sperling is a distinguished professor of civil engineering and environmental science and policy at the University of California at Davis, where he is also founding director of the school’s Institute of Transportation Studies. Sperling, a member of the California Air Resources Board, recently gave a talk at MITEI detailing major technological and societal developments that have the potential to change transportation for the better — or worse. Following the event, Sperling spoke to MITEI about policy, science, and how to harness these change agents for the public good.
(Sperling’s talk is also available as a podcast.)
Q: What are the downsides of the “car-centric monoculture,” as you put it, that we find ourselves living in?
A: Cars provide great value, which is why they are so popular. But too much of a good thing can be destructive. We’ve gone too far. We’ve created a transportation system made up of massive road systems and parking infrastructure that is incredibly expensive for travelers and for society to build and maintain. It is also very energy- and carbon-intensive, and disadvantages those unable to buy and drive cars.
Q: Can you tell me about the three transportation revolutions that you say are going to transform mobility over the next few decades?
A: The three revolutions are electrification, automation, and pooling. Electrification is already under way, with increasing numbers of pure battery electric vehicles, plug-in hybrid vehicles that combine batteries and combustion engines, and fuel cell electric vehicles that run on hydrogen. I currently own a hydrogen car (Toyota Mirai) and have owned two different battery electric cars (Nissan Leaf and Tesla).
A second revolution, automation, is not yet under way, at least in the form of driverless cars. But it is poised to be truly transformational and disruptive for many industries — including automakers, rental cars, infrastructure providers, and transit operators. While partially automated cars are already here, true transformations await fully driverless vehicles, which are not likely to exist in significant numbers for a decade or more.
Perhaps the most pivotal revolution, at least in terms of assuring that the automation revolution serves the public interest, is pooling, or sharing. Automation without pooling would lead to large increases in vehicle use. With pooling, though, automation would lead to reductions in vehicle use, but increases in mobility (passenger miles traveled) by mobility-disadvantaged travelers who are too poor or disabled to drive.
Q: You’ve mentioned that how these revolutions play out depends on which cost factor dominates — money or time. The result would either be heaven or hell for our environment and cities. Explain the nuances of that situation.
A: With pooled, automated and electric cars, the cost of travel would drop precipitously as a result of using cars intensively — spreading costs over 100,000 miles or more per year — having no driver costs, and having multiple riders share the cost. The monetary cost could be as little as 15 cents per mile, versus 60 cents per mile for an individually-owned automated car traveling 15,000 miles per year. The time cost of car occupants, on the other hand, is near zero because they don’t need to pay attention to driving. They can work, sleep, text, drink, and read. Thus, even if the cost of owning and operating the vehicle is substantial, the time savings would be so beneficial that many, perhaps most, would choose car ownership over subscribing to an on-demand service. In fact, most people in affluent countries would likely choose the huge time savings, worth $10, $20, or more per hour, over low travel costs. Thus, policy will be needed to assure that the public interest — environmental externalities, urban livability, access by the mobility disadvantaged — is favored over the gains of a minority of individuals.
A drone, also called an unmanned aerial automobile (UAV) as well as many other names, is a device that will fly without the use of a pilot or any individual aboard. These ‘aircraft’ could be managed from another location making use of a remote control tool by a person standing on the ground or by using computers that are on-board. UAV’s initially were usually controlled by someone on the ground but as modern technology has progressed, increasingly more aircraft are being made with the aim of being controlled through on-board computer systems.
The idea of an unmanned aerial vehicle could be traced back to early in the twentieth century as well as were originally planned to be solely made use of for armed forces missions yet have since found location in our daily lives. Reginald Denny, that was a preferred movie celebrity along with an avid collection agency of design planes was claimed to create the very first remote piloted car in 1935. Given that this date, the aircraft have had the ability to adjust to brand-new technologies and could currently be found with electronic cameras as well as other valuable bonus. As an outcome of this, UAVs are utilized for policing, safety work as well as monitoring and firefighting, they are also made use of by lots of firms to look at hard to get to possessions such as piping as well as wirework adding an added layer of safety and protection.
The increase in popularity of these tools has however, brought some downsides in addition to positives as new policies as well as regulations have had to be presented to manage the circumstance. As the UAVs were getting more powerful as well as innovations were enhancing, it meant that they could fly greater and additionally away from the operator. This has actually led to some problems with flight terminal interference all over the world. In 2014, South Africa introduced that they needed to tighten up security when it comes to unlawful flying in South African airspace. A year later as well as the US announced that they were holding a meeting to review the needs of signing up a commercial drone.
As well as the previously discussed uses, drones are currently likewise made use of for surveying of plants, counting animals in a certain location, evaluating a group amongst many others. Drones have managed to change the manner in which numerous markets are run and also have additionally allowed many organisations to come to be more efficient. Drones have also assisted to boost safety and also contribute when it comes to saving lives. Woodland fires as well as all-natural calamities can be kept track of and also the drone can be utilized to signal the pertinent authorities of any person that is in problem and also looking for help. The exact location of these events can also be discovered easily.
Drones have additionally come to be a leisure activity for many individuals worldwide. In the United States, entertainment use of such a device is lawful; nonetheless, the owner needs to take some preventative measures when trying to fly. The aircraft has to abide by specific guidelines that have actually been set out; for instance, the tool can not be greater than 55 pounds. The drone must also prevent being used in such a way that will hinder airport terminal procedures and also if a drone is flown within 5 miles of an airport terminal, the airports traffic control tower should be warned in advance.
A drone, also referred to as an unmanned airborne automobile (UAV) as well as several various other names, is a gadget that will fly without the use of a pilot or any person aboard. These ‘aircraft’ can be regulated from another location using a push-button control device by somebody standing on the ground or by using computers that are on-board. UAV’s initially were usually regulated by a person on the ground however as technology has advanced, an increasing number of airplane are being made with the goal of being managed using on-board computers.
The concept of an unmanned airborne vehicle can be mapped back to early in the twentieth century and were initially planned to be entirely made use of for armed forces objectives but have actually given that found area in our daily lives. Reginald Denny, that was a prominent film star along with an enthusiastic enthusiast of design planes was said to produce the first ever remote piloted automobile in 1935. Given that this day, the airplane have actually had the ability to adjust to brand-new innovations and can now be discovered with cams in addition to various other valuable additionals. As a result of this, UAVs are utilized for policing, security work and also security and firefighting, they are also utilized by several firms to look at hard to reach assets such as piping and wirework adding an extra layer of safety and security and also protection.
The increase in popularity of these gadgets has nevertheless, brought some downsides along with positives as new rules and also guidelines have had to be presented to manage the situation. As the UAVs were getting more powerful as well as modern technologies were enhancing, it implied that they might fly greater and also better far from the driver. This has actually brought about some difficulties with airport terminal interference throughout the world. In 2014, South Africa introduced that they had to tighten protection when it concerns illegal flying in South African airspace. A year later on as well as the US announced that they were holding a meeting to talk about the demands of signing up a business drone.
In addition to the previously mentioned usages, drones are now additionally made use of for evaluating of plants, counting pets in a particular area, looking into a group amongst several others. Drones have actually managed to change the manner in which lots of industries are run as well as have likewise enabled many services to become extra effective. Drones have actually also assisted to boost security as well as contribute when it concerns saving lives. Forest fires and also natural calamities could be kept track of as well as the drone could be utilized to inform the appropriate authorities of anyone that remains in problem and in need of assistance. The exact area of these occasions can also be discovered easily.
Drones have additionally become a leisure activity for many people around the globe. In the US, leisure use such a device is lawful; nevertheless, the owner has to take some precautions when trying to fly. The airplane needs to stick to particular guidelines that have been outlined; for instance, the tool can not be more than 55 extra pounds. The drone ought to also prevent being used in such a way that will certainly interfere with airport operations and if a drone is flown within 5 miles of an airport, the flight terminals traffic control tower should be alerted in advance.
The very early days of a start-up are iterative. Improving an item calls for much testing as well as insight from your user base. To browse these early days efficiently, you’ll need information. As a result, social media communities are necessary for startups. An energetic, engaged area is excellent for getting responses and learning their requirements. With a social media community, you gain details that makes your item much better.
Areas provide customers a sense of company with the start-up. They also drive a start-up’s development. This, subsequently, gives start-ups an affordable benefit.
HOW AREA SPURS GROWTH
A Start-up Social network Area Motivates Ministration
By using an enthusiastic team, you accumulate a culture of brand name evangelists as well as ambassadors. These customers drum up buzz and also exhilaration for your brand name across the web. With a community of evangelists, your startup becomes a full-fledged motion.
Social network Communities Welcome Newcomers
Start-ups may use their areas as a support network to repair for new customers. This offsets the troubleshooting tons for a tiny start-up team. As a bonus offer, specifically practical individuals will really feel extra connected to the brand. This group could additionally offer crucial testimonials and testimonies.
A Strong Social Media Community = Competitive Advantage
Allow’s claim your start-up is making waves, and competitors emerges. It’s easy to duplicate item attributes. On the other hand, duplicating community is an entire various story. If you’ve built a devoted social media sites startup community, its individuals will stick up for your company. This gives you an advantage over the competition.
WHERE TO BEGINNING BUILDING FANS
Select the Right Social Platform
Since nobody social media network is king, you must create a multi-channel method. That stated, it’s best to choose 2 or 3 systems to concentrate on when beginning.
This does not should be a hard decision. A style brand name, for instance, would find a natural fit on visually focused Instagram. Expand your base upon your 2 or 3 platforms of selection. As soon as you have actually mastered those, extend to more.
Usage Your Social network Community to Educate
Setting up a how-to channel assists novices feel welcome. It also supplies a place for your group to share pointers with each other. You could begin by writing tutorials to help customers comprehend your product. Welcome others to share their stories as well as how-tos. A collective team equips your clients.
If you desire an instance of such a community, have a look at the Stone subreddit on Reddit. Here, clients and Stone employees help each other out with the firm’s products. They continue to do so long after the firm was acquired by Fitbit.
Start Discussion in a Social Community by Facilitating It
Ideally, you desire a team that maintains itself with a base of individuals producing handy as well as interesting material for one another. First, you should get the ball rolling by posting web content of your own. Begin by concentrating on the start-up’s core worths. Once you have actually demonstrated how your brand sees things, urge others to jump in!
Don’t Shy Away from Dispute
Keep in mind the old Mac vs COMPUTER discussion (or, more recently, the Android vs iOS one)? A bit of pleasant competition does a whole lot to stimulate community development. Allow your advocates to reveal their love for your brand name authentically. As long as conversation fits within core start-up values, the neighborhood might be motivated by competitors and also move growth.
Keep Your Fans Safe
All of us desire a thriving social networks start-up neighborhood, however it comes with a cost. A lot of task suggests a great deal of discussions to modest. It can be hard for brand-new organisations to moderate a start-up community on social media. Thankfully, with the right devices, you could maintain your followers secure more easily.
Smart Small amounts is a device that automatically identifies and also removes troublesome language within the min it’s published. With innovative machine learning, your team could guarantee a safe, inviting group without any added work. The device functions throughout numerous platforms as well as calls for no coding knowledge or experience. Have a look at just what sets it in addition to various other tools below, as well as find out exactly how you can develop an incredible group for a start-up!
Social MediaSocial media communitiesSocial media area social networks startup communityStartup area
The early days of a startup are iterative. Perfecting an item requires much testing and insight from your customer base. To navigate these very early days efficiently, you’ll need data. For that reason, social media areas are essential for startups. An energetic, engaged community is perfect for receiving feedback as well as discovering their needs. With a social media neighborhood, you gain info that makes your item better.
Communities offer individuals a sense of agency with the startup. They likewise drive a startup’s development. This, in turn, provides startups an affordable benefit.
HOW NEIGHBORHOOD STIMULATES DEVELOPMENT
A Start-up Social media site Community Urges Evangelism
By using a passionate group, you develop a society of brand name evangelists and ambassadors. These users attract buzz and also exhilaration for your brand throughout the net. With an area of evangelists, your start-up becomes a full-fledged activity.
Social Media Communities Invite Newcomers
Start-ups might utilize their neighborhoods as a support network to troubleshoot for new individuals. This offsets the troubleshooting lots for a little startup group. As a bonus offer, specifically practical individuals will certainly feel a lot more attached to the brand name. This team might additionally give vital testimonials and also reviews.
A Solid Social media site Neighborhood = Affordable Benefit
Let’s say your start-up is making waves, as well as competitors arises. It’s very easy to copy item functions. On the other hand, replicating community is an entire different tale. If you have actually built a dedicated social media start-up area, its customers will certainly stick up for your business. This gives you an advantage over the competitors.
WHERE TO START BUILDING FOLLOWERS
Select the Right Social Platform
Due to the fact that no one social media is king, you must establish a multi-channel method. That said, it’s finest to choose 2 or 3 systems to focus on when starting.
This doesn’t should be a difficult decision. A fashion brand, as an example, would certainly locate a natural fit on aesthetically focused Instagram. Grow your base on your 2 or 3 platforms of choice. As soon as you have actually mastered those, reach extra.
Use Your Social network Community to Instruct
Establishing a how-to network helps beginners really feel welcome. It also supplies an area for your group to share pointers with each other. You can start by creating tutorials to help users comprehend your product. Invite others to share their tales as well as how-tos. A collective team equips your clients.
If you desire an example of such an area, look into the Stone subreddit on Reddit. Here, consumers and Pebble staff members help each other out with the business’s products. They remain to do so long after the business was acquired by Fitbit.
Begin Discussion in a Social Area by Promoting It
Ideally, you want a team that maintains itself with a base of individuals producing handy and appealing material for each other. Initially, you need to obtain the sphere rolling by posting material of your personal. Begin by focusing on the startup’s core values. When you’ve shown how your brand name sees points, encourage others to jump in!
Do not Shy Away from Conflict
Remember the old Mac vs PC discussion (or, a lot more lately, the Android vs iOS one)? A little bit of friendly competition does a lot to spur neighborhood growth. Permit your fans to reveal their love for your brand authentically. As long as discussion fits within core start-up worths, the area could be encouraged by competitors as well as thrust growth.
Keep Your Fans Safe
We all want a prospering social media sites start-up neighborhood, but it comes at an expense. A great deal of task indicates a lot of conversations to modest. It could be tough for new services to regulate a start-up community on social networks. Luckily, with the right tools, you can keep your fans risk-free much more easily.
Smart Small amounts is a device that immediately finds as well as erases troublesome language within the min it’s uploaded. With sophisticated artificial intelligence, your team can guarantee a safe, welcoming group without any added work. The device works across several platforms as well as calls for no coding understanding or experience. Look into what establishes it aside from various other tools here, and learn exactly how you can construct an outstanding team for a startup!
Social MediaSocial media communitiesSocial media community social media startup communityStartup neighborhood
ARTIFICIAL INTELLIGENCE ADVERTISING IS CHANGING THE GAME
In the event of a natural disaster that disrupts phone and Internet systems over a wide area, autonomous aircraft could potentially hover over affected regions, carrying communications payloads that provide temporary telecommunications coverage to those in need.
However, such unpiloted aerial vehicles, or UAVs, are often expensive to operate, and can only remain in the air for a day or two, as is the case with most autonomous surveillance aircraft operated by the U.S. Air Force. Providing adequate and persistent coverage would require a relay of multiple aircraft, landing and refueling around the clock, with operational costs of thousands of dollars per hour, per vehicle.
Now a team of MIT engineers has come up with a much less expensive UAV design that can hover for longer durations to provide wide-ranging communications support. The researchers designed, built, and tested a UAV resembling a thin glider with a 24-foot wingspan. The vehicle can carry 10 to 20 pounds of communications equipment while flying at an altitude of 15,000 feet. Weighing in at just under 150 pounds, the vehicle is powered by a 5-horsepower gasoline engine and can keep itself aloft for more than five days — longer than any gasoline-powered autonomous aircraft has remained in flight, the researchers say.
The team is presenting its results this week at the American Institute of Aeronautics and Astronautics Conference in Denver, Colorado. The team was led by R. John Hansman, the T. Wilson Professor of Aeronautics and Astronautics; and Warren Hoburg, the Boeing Assistant Professor of Aeronautics and Astronautics. Hansman and Hoburg are co-instructors for MIT’s Beaver Works project, a student research collaboration between MIT and the MIT Lincoln Laboratory.
A solar no-go
Hansman and Hoburg worked with MIT students to design a long-duration UAV as part of a Beaver Works capstone project — typically a two- or three-semester course that allows MIT students to design a vehicle that meets certain mission specifications, and to build and test their design.
In the spring of 2016, the U.S. Air Force approached the Beaver Works collaboration with an idea for designing a long-duration UAV powered by solar energy. The thought at the time was that an aircraft, fueled by the sun, could potentially remain in flight indefinitely. Others, including Google, have experimented with this concept, designing solar-powered, high-altitude aircraft to deliver continuous internet access to rural and remote parts of Africa.
But when the team looked into the idea and analyzed the problem from multiple engineering angles, they found that solar power — at least for long-duration emergency response — was not the way to go.
“[A solar vehicle] would work fine in the summer season, but in winter, particularly if you’re far from the equator, nights are longer, and there’s not as much sunlight during the day. So you have to carry more batteries, which adds weight and makes the plane bigger,” Hansman says. “For the mission of disaster relief, this could only respond to disasters that occur in summer, at low latitude. That just doesn’t work.”
The researchers came to their conclusions after modeling the problem using GPkit, a software tool developed by Hoburg that allows engineers to determine the optimal design decisions or dimensions for a vehicle, given certain constraints or mission requirements.
This method is not unique among initial aircraft design tools, but unlike these tools, which take into account only several main constraints, Hoburg’s method allowed the team to consider around 200 constraints and physical models simultaneously, and to fit them all together to create an optimal aircraft design.
“This gives you all the information you need to draw up the airplane,” Hansman says. “It also says that for every one of these hundreds of parameters, if you changed one of them, how much would that influence the plane’s performance? If you change the engine a bit, it will make a big difference. And if you change wingspan, will it show an effect?”
Framing for takeoff
After determining, through their software estimations, that a solar-powered UAV would not be feasible, at least for long-duration use in any part of the world, the team performed the same modeling for a gasoline-powered aircraft. They came up with a design that was predicted to stay in flight for more than five days, at altitudes of 15,000 feet, in up to 94th-percentile winds, at any latitude.
In the fall of 2016, the team built a prototype UAV, following the dimensions determined by students using Hoburg’s software tool. To keep the vehicle lightweight, they used materials such as carbon fiber for its wings and fuselage, and Kevlar for the tail and nosecone, which houses the payload. The researchers designed the UAV to be easily taken apart and stored in a FedEx box, to be shipped to any disaster region and quickly reassembled.
This spring, the students refined the prototype and developed a launch system, fashioning a simple metal frame to fit on a typical car roof rack. The UAV sits atop the frame as a driver accelerates the launch vehicle (a car or truck) up to rotation speed — the UAV’s optimal takeoff speed. At that point, the remote pilot would angle the UAV toward the sky, automatically releasing a fastener and allowing the UAV to lift off.
In early May, the team put the UAV to the test, conducting flight tests at Plum Island Airport in Newburyport, Massachusetts. For initial flight testing, the students modified the vehicle to comply with FAA regulations for small unpiloted aircraft, which allow drones flying at low altitude and weighing less than 55 pounds. To reduce the UAV’s weight from 150 to under 55 pounds, the researchers simply loaded it with a smaller ballast payload and less gasoline.
In their initial tests, the UAV successfully took off, flew around, and landed safely. Hoburg says there are special considerations that have to be made to test the vehicle over multiple days, such as having enough people to monitor the aircraft over a long period of time.
“There are a few aspects to flying for five straight days,” Hoburg says. “But we’re pretty confident that we have the right fuel burn rate and right engine that we could fly it for five days.”
“These vehicles could be used not only for disaster relief but also other missions, such as environmental monitoring. You might want to keep watch on wildfires or the outflow of a river,” Hansman adds. “I think it’s pretty clear that someone within a few years will manufacture a vehicle that will be a knockoff of this.”
This research was supported, in part, by MIT Lincoln Laboratory.