There are discussions among neuroscientists, cognitionists and philosophers about whether the human brain can be created or reconstructed. Current breakthroughs and discoveries in brain science are steadily paving the way for a time when artificial brains can be recreated from scratch. Some people assume that it is beyond the bounds of the possible, the second are busy with ways to create it, the third have been working fruitfully on the task for a long time. In the article, we will consider questions about the development of artificial intelligence, its prospects, as well as large companies and projects in this area.
Basics
The artificial brain corresponds to a robotic machine that is as smart, creative and conscious as humans. In the entire history of mankind, the task has not been fully resolved, but the futurists say that this is a matter of time. Considering moderntrends in neuroscience, computing and nanotechnology predict that artificial intelligence and the brain will emerge in the 21st century, possibly by 2050.
Scientists are considering several ways to create artificial intelligence. In the first case, large-scale biologically realistic simulations of the human brain are carried out on supercomputers. In the second case, scientists are trying to create massively parallel neuromorphic computing devices that are easily modeled on neural tissue.
Human consciousness in terms of the most interesting mysteries of science and metaphysics is considered the most complex and most achievable. Similar conclusions are reached by reverse engineering the human brain.
Machine learning
Machine learning is at the heart of the development strategy of "artificial intelligence", for this, human brain cells are comprehensively studied. This type of learning has great potential: its platform includes algorithms, development tools, APIs, and model deployment. Computers have the ability to learn without being explicitly programmed. Innovative companies Amazon, Google and Microsoft are actively using machine learning.
Deep learning platforms
Deep learning is part of machine learning. It is based on how the human brain works and relies on artificial neural network (ANN) algorithms through which information flows. Robots can "learn" from inputs and results. Deep Learning - Promisingtrend in artificial intelligence, combined with large amounts of information. It has proven itself in pattern recognition and classification. Deep Instinct, Fluid AI, MathWorks, Ersatz Labs, Sentient Technologies, Peltarion and Saffron Technology are examples of companies that are pioneers in this field of intelligence study.
Natural Language Processing
Neuro-linguistic programming (NLP) is on the border between computer and human language and is an artificial intelligence technology. Computer programs can understand spoken or written human speech. In the Amazon Alexa software, Apple Siri, Microsoft Cortana, and Google Assistant, NLP is used to understand user questions and provide answers to them. This type of programming is widely used in economic transactions and customer service.
Natural Language Generation
NLG software is used to convert all kinds of data into human readable text, this is achieved through the study of the brain. It is an underrated technology with applications like business intelligence report automation, product descriptions, financial reports. Technology makes it possible to create user-generated content at a predictable additional cost. Structured data is converted to text at high speed, up to several pages per second. Interesting players in this market are Automated Insights,Lucidworks, Attivio, SAS, Narrative Science, Digital Reasoning, Yseop and Cambridge Semantics.
Virtual Agents
In the framework of artificial intelligence technologies, the terms "virtual agent" and "virtual assistant" are not interchangeable. Some people try to distinguish between concepts, and they succeed.
Virtual Assistant is a kind of personal online assistant. Virtual agents are often represented as computer AI characters having an intelligent conversation with users. They can answer questions and their main advantage is that clients can get help 24 hours a day.
Speech recognition
Speech identification is the ability of a program to understand and analyze words and phrases in spoken language, and convert them into data using the built-in artificial brain algorithm. Speech recognition is used in the company for call routing, voice dialing, voice search, and speech-to-text processing. One disadvantage is that the program can confuse words due to differences in pronunciation and background noise. Speech recognition software is increasingly installed on mobile devices. Nuance Communications, OpenText, Verint Systems and NICE are developing in this area.
AI-embedded hardware
Devices with embedded AI, chips and graphics processing units (GPUs) have become widespread. Google has built into itshardware artificial intelligence, taking as a basis the development of the institute of the human brain. The impact of integrating AI with software goes far beyond consumer applications such as entertainment and gaming. This is a new type of technology that will be used to advance deep learning. Such developments are carried out by Google, IBM, Intel, Nvidia, Allluviate and Cray.
Decision Management
Business decision management in innovative products (eg robot with artificial intelligence) covers all aspects of the design and regulation of automated systems. It is essential for organizations to manage interactions between employees, customers and suppliers.
Decision management improves the process of alternative choice, here all possible information is used for the best preference, while the emphasis is on maneuverability, consistency, accuracy of decision making. Decision management takes into account time constraints and known risks.
Banking, insurance and financial services organizations are integrating day-to-day decision software into their customer service processes.
Neuromorphic equipment
SyNAPSE is a DARPA-fundedprogram to develop neuromorphic microprocessor systems that map to brain intelligence and physics. The platform is looking for an answer to the main question: is it possible to create an artificial brain? At firstneural networks are tested in simulations on a supercomputer, then networks are built directly in hardware. In October 2011, a prototype neuromorphic chip containing 256 neurons was demonstrated. Work is underway to create a multi-chip system capable of emulating 1 million peak neurons and 1 billion synapses.
Neural network modeling
The Blue Brain Project is an attempt to reconstruct the human brain and spinal cord using computer simulations at the molecular level. The project was founded in May 2005 by Henry Markram at the State Polytechnic School of Lausanne (EPFL) in Switzerland. The simulation runs on the IBM Blue Gene supercomputer, hence the name Blue Brain. As of November 2018, simulations are being carried out on mesocytes containing about 10 million neurons and 10 billion synapses. A full-scale simulation of the human brain with its 186 billion neurons is scheduled for 2023.
Spaun, a unified network with a semantic pointer architecture, was created by Chris Eliasmit and colleagues at the Center for Theoretical Neuroscience (CTN) at the University of Waterloo in Canada. As of December 2018, Spaun is the world's largest brain simulation. The model contains 2.5 million neurons, which is enough for it to recognize lists of numbers, perform simple calculations.
SpiNNaker is a massive low power neuromorphic supercomputer thatcurrently under construction at the University of Manchester in the UK. With over a million cores and a thousand simulated neurons, the machine would be capable of simulating one billion neurons. Instead of implementing one specific algorithm, SpiNNaker will become a platform where you can test different algorithms. Different types of neural networks can be designed and run on a machine, thus simulating different types of neurons and communication patterns. SpiNNaker is an acronym derived from Spi King Nural.
Brain Corporation is a small research company that develops new algorithms and microprocessors that underlie the biological nervous system. The company was founded in 2009 by computational neuroscientist Evgeny Izhikevich and neuroscientist/entrepreneur Allen Gruber. Their research focuses on the following areas: visual perception, motor control and autonomous navigation. The company's goal is to equip consumer devices such as mobile phones and household robots with an artificial nervous system. The study is funded in part by Qualcomm, which is located on the Qualcomm campus in San Diego, California. No specific products have yet been released or announced, but the company continues to grow and has been actively hiring new employees since February 2018.
Related Research
Google X Lab is a secret lab where Google experiments with future technologies. Projects on which the companyworks are not publicly available, but are believed to be based on robotics and artificial intelligence. Details about the lab first appeared in a New York Times article in November 2011. The publication states that the laboratory is located in the Bay Area, California. It is well known that the founders of Google are interested in studying artificial intelligence and are investing in this direction. In 2006, a company memo said that Google wanted to build the world's best AI research lab.
Russia 2045, known as the 2045 Initiative or the Avatar Project, is an ambitious long-term project that aims to have robotic avatars by 2020, brain transplants by 2025, and artificial brains by 2035. The program was launched in 2011 by Russian media mogul Dmitry Itskov. It aims to create a human brain institution through a global network of scientists who work together for the benefit of humanity and the systematic development of technology. A number of Russian scientists have already received investments from Itskov for their research. In addition, Itskov is seeking additional funding from high net worth individuals, charities, and national and international governments.
The next interesting project is a Boston University and Hewlett Packard (HP) program called Moneta. The HP team, led by Greg Snyder, is building a neural network platform called Cog Ex Machina that canwork in GPUs and computers of the future based on memristors. The Neuromorphology Lab at Boston University, led by Massimiliano Versace, has created a modular artificial brain, Moneta, that runs on Cog Ex Machina. The acronym stands for Modular Neural Exploring Travel Agent.
Time Frame
The question inevitably arises as to when a digital copy of the brain and spinal cord can be synthesized.
Unfortunately, this will not come soon. Kurzweil's prediction of brain emulation by 2030 seems overly short, just 12 years away. Moreover, his analogies with the Human Genome Project proved unsatisfactory. In addition, many scientists are probably moving in some dead end directions.
Similarly, Goertzel's predictions about the success of the rule-based approach over the next decades seem overly optimistic. Though probably not impossible given his AI training approach.
According to the likely scenario, the creation of a code or a semblance of a human brain is possible in 50-75 years. Nevertheless, the date is rather difficult to predict, given the margin of error in neuroscience, on the one hand, and the speed of change, on the other. 2050 is kind of a black hole when it comes to predictions.
