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5 industries that will see a staggering adoption of Machine Learning in 2021 – Express Computer

By Amit Gupta

Machine learning is one of the most disruptive technologies that we have encountered in our generation. It has the great potential to transform businesses for better. From being a niche technology, ML is now seeing increased adoption among organisations in various sectors.

Across the globe, brands are leveraging ML to drive innovation and better customer experience. Nike, for example, uses ML for personalised product recommendation. Dominos ensures 10 minutes or less pizza delivery time using ML technologies. Another popular example is how BMW Group uses ML to read data from vehicle subsystems and predict the performance of vehicle parts and proactively recommend maintenance.

ML emerged as a key priority area for technology leaders in 2020 itself as they aim to achieve revenue growth while reducing costs. In 2021, enterprises are exploring more matured use cases of the technology as they navigate an environment of flux. Disruptive organisations have been at the forefront of adopting this technology across areas for process automation, customer experience, security and others.

In 2021, here are top five industries that will adopt ML to change forever the way they work.

Healthcare: The global pandemic has underscored the importance of investing on and optimising our healthcare systems. ML is considered to be the most promising technology that allows healthcare providers to churn the massive volumes of data and derive valuable clinical insights. ML offers huge progress in drug discovery, cutting down the long discovery and development pipeline and reducing cost. It can also significantly improve healthcare delivery systems and in turn lift the overall quality of healthcare while keeping cost under control. In the days to come, ML is predicted to have critical application in clinical trials as well. ML is going to have huge impact on almost all branches of healthcare including pharma and biotech, experts emphasize.

Banking & finance: Banking sector has already seen many matured use cases of ML especially in fraud detection and automating processes. ML use cases will be actively explored across areas such as trading, investment modeling, risk prevention and customer sentiment analysis. As digital transactions continue to grow, ML combined with predictive analytics will play a big role in helping financial institutions to improve transaction efficiencies throughout the transaction lifecycle. Banks and financial institutions will also use this technology to customise their products and offerings to stay more relevant in a competitive environment.

Media & entertainment: Companies like Amazon and Netflix have already popularised the data-driven content consumption models in recent years. As the global pandemic further drives up the demand for new consumption models, firms will effectively leverage AI and ML to create value for customers and present the most relevant content to them in real-time. Whether its developing better recommendation engines or deliver hyper-targeted services, ML is going to be critical for the media and entertainment industry to address the drastically changing customer expectations. Predictive modelling will be key in responding to customers in real-time, anticipating the future demand and making investments wisely.

Retail and ecommerce: No other industry has better understood the need to be prepared for the unexpected. The global pandemic has disrupted the retail sector in several ways and ML has been looked upon as a key enabler for the sector to effectively address change. Whether it is the traditional brick-and-mortar stores or the ecommerce companies, the sector is on a path to reinvention with technologies such ML. Starting from supply chain and inventory management to personalised product recommendations through chatbots, the retail and ecommerce sector is looking at several ML use cases. It is also being used extensively for predicting user behavior and analysing the trend effectively to be better prepared. Dynamic pricing is emerging as a key ML use case, to help retailers thrive in a competitive market landscape.

Manufacturing & Industry 4.0: With the massive adoption of IoT devices set to further increase in the manufacturing sector, ML will be the most critical technology bridge that analyses the huge volumes of data generated. ML serves as the powerful building block of Industry 4.0 along with automation and data connectivity. While predictive maintenance is the most explored use case so far, manufacturers will look at more matured use cases of ML such as real-time error detection, supply chain visibility, warehousing efficiency and cost reduction, asset tracking among others. As traditional factories transform into smart factories, ML will fuel greater innovation and efficiency in the days to come.

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Sift to Host Live Virtual Event Featuring Gartner Analysts on Machine Learning-powered Fraud Detection, Creating Trust and Safety on the Internet -…

SAN FRANCISCO, April 06, 2021 (GLOBE NEWSWIRE) -- Sift, the leader in Digital Trust & Safety, today announced that it will be hosting a virtual event on April 20, 2021, with Gartner analysts presenting new research in two live-only sessions: How to Select a Machine Learning Vendor for Fraud Detection in Online Retail, and Create Trust and Safety on the Internet.

During the sessions, Gartner Senior Director Analysts Dr. Akif Khan, Ph.D, and Jonathan Care will explore the challenges presented by todays interconnected digital Fraud Economy, which can easily overwhelm fraud teams restricted by limited resources, disparate tools, or a narrow strategy focused on a single abuse type. Led by Sift Trust and Safety Architect Kevin Lee, the sessions will provide actionable steps merchants can take to prevent inaccurate transaction decisioning, rising chargebacks and false positives, unnecessary friction for trusted users, and ultimately, lost revenue.

Lee and the Gartner analysts will also answer live questions from attendees.

As cybercriminals adapt and become more sophisticated, fraud fighters can only defend their organizations by staying one step ahead of them, said Lee. Our virtual event featuring Gartner will arm fraud prevention and trust and safety teams with the guidance they need to not only prevent fraud but create a streamlined experience for trusted customers the foundation of a Digital Trust & Safety strategy.

To see full details and to sign up for the live virtual event, go to https://pages.sift.com/gartner-event-2021.html.

About Sift

Sift is the leader in Digital Trust & Safety, empowering digital disruptors to Fortune 500 companies to unlock new revenue without risk. Sift dynamically prevents fraud and abuse through industry-leading technology and expertise, an unrivaled global data network of 70 billion events per month, and a commitment to long-term customer partnerships. Global brands such as Twitter, Airbnb, and Wayfair rely on Sift to gain a competitive advantage in their markets. Visit us at sift.com and follow us on Twitter @GetSift.

Media ContactVictor WhiteDirector of Corporate Communications, Siftvwhite@siftscience.com

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TigerGraph’s Graph + AI Summit 2021 to Feature 40+ Sessions, Live Workshops and Speakers from JPMorgan Chase, NewDay, Pinterest, Jaguar Land Rover and…

REDWOOD CITY, Calif., April 08, 2021 (GLOBE NEWSWIRE) -- TigerGraph, provider of the leading graph analytics platform, today unveiled the complete agenda for Graph + AI Summit 2021, the industrys only open conference devoted to democratizing and accelerating analytics, AI and machine learning with graph algorithms. The roster includes confirmed speakers from JPMorgan Chase, Intuit, NewDay, Jaguar Land Rover, Pinterest, Stanford University, Forrester Research, Accenture, Capgemini, KPMG, Intel, Dell, and Xilinx, as well as many innovative startups including John Snow Labs, Fintell, SaH Solutions and Sayari Labs. The virtual conference, set for April 21-23, offers keynotes, speakers, real-world customer case studies and hands-on workshops for data, analytics and AI professionals.

The combination of analytics, AI, machine learning and graph is a powerful one that offers many human benefits and forward-looking companies in all industries have taken note, said Dr. Yu Xu, founder and CEO of TigerGraph. Graph + AI Summit is again bringing together industry luminaries, technical experts and business leaders from the worlds largest banks, fintechs, tech giants and manufacturers to share implementation best practices, lessons learned and more. Were pleased to welcome back speakers from Jaguar Land Rover and Intuit, and welcome new participants from an impressive list of todays top innovators driving the adoption of graph. Our goal is to make graph accessible, applicable and understandable for all, as more people grasp how graph-related technologies can improve our lives.

Graph + AI Summit returns after a successful Graph + AI 2020; the inaugural event attracted more than 3,000 attendees from 56 countries, and welcomed data scientists, data engineers, architects and business and IT executives from 115 of the Fortune 500 companies. The latest conference will host over 6,000 attendees this year and again focus on accelerating analytics, AI and machine learning with graph algorithms timely technologies that are on the minds of todays business leaders. After 2020 accelerated enterprises shift to the cloud, businesses are realizing graph technologies are key to connecting, analyzing and helping glean insights from data.

Graph + AI Summit 2021 includes keynote presentations, executive roundtables, technical breakout sessions, industry tracks (banking, insurance and fintech, healthcare, life sciences and government) and live workshops for advanced analytics and machine learning.

Keynote speakers presenting during conference general sessions include:

Notable roundtables and interactive sessions include:

Graph + AI Summit sessions will also cover the following topics:

Register for one of these live workshops for advanced analytics and machine learning now:

View Graph + AI Summits agenda: https://www.tigergraph.com/graphaisummit/#day1Register and secure your complimentary spot: https://www.tigergraph.com/graphaisummit/.

Helpful Links

About TigerGraphTigerGraph is a platform for advanced analytics and machine learning on connected data. Based on the industrys first and only distributed native graph database, TigerGraphs proven technology supports advanced analytics and machine learning applications such as fraud detection, anti-money laundering (AML), entity resolution, customer 360, recommendations, knowledge graph, cybersecurity, supply chain, IoT, and network analysis. The company is headquartered in Redwood City, California, USA. Start free with tigergraph.com/cloud.

Media ContactCathy WrightOffleash PR for TigerGraphcathy@offleashpr.com650-678-1905

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AI and Machine Learning Operationalization Software Market to Witness Stellar CA – Business-newsupdate.com

AI and Machine Learning Operationalization Software Market to Witness Stellar CAGR During the Forecast Period 2021 -2026

The Global AI and Machine Learning Operationalization Software Market report draws precise insights by examining the latest and prospective industry trends and helping readers recognize the products and services that are boosting revenue growth and profitability. The study performs a detailed analysis of all the significant factors, including drivers, constraints, threats, challenges, prospects, and industry-specific trends, impacting the AI and Machine Learning Operationalization Software market on a global and regional scale. Additionally, the report cites worldwide market scenario along with competitive landscape of leading participants.

The recent study on AI and Machine Learning Operationalization Software market offers a detailed analysis of this business vertical by expounding the key development trends, restraints & limitations, and opportunities that will influence the industry dynamics in the coming years. Proceeding further, it sheds light on the regional markets and identifies the top areas to further business development, followed by a thorough scrutiny of the prominent companies in this business sphere. Additionally, the report explicates the impact of the Covid-19 pandemic on the profitability graph and highlights the business strategies adopted by major players to adapt to the instabilities in the market.

Major highlights from the Covid-19 impact analysis:

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An overview of the regional analysis:

Additional highlights from the AI and Machine Learning Operationalization Software market report:

Strategic Points Covered in Table of Content of Global AI and Machine Learning Operationalization Software Market:

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Apple Reveals a Multi-Mode Planar Engine for a Neural Processor that could be used in A-Series & screamingly fast M1 Processors – Patently Apple

Back in 2017, Apple introduced the A11 which included their first dedicated neural network hardware that Apple calls a "Neural Engine." At the time, Apple's neural network hardware was able to perform up to 600 billion operations per second and used for Face ID, Animoji and other machine learning tasks. The neural engine allows Apple to implement neural network and machine learning in a more energy-efficient manner than using either the main CPU or the GPU. Today Apple's Neural Engine has advanced to their new M1 processor that delivers 15X faster machine learning performance of the Neural Engine, according to Apple.

Apple revealed back in Q4 that the "M1 features their latest Neural Engine. Its 16core design is capable of executing a massive 11 trillion operations per second. In fact, with a powerful 8core GPU, machine learning accelerators and the Neural Engine, the entire M1 chip is designed to excel at machine learning." There's an excellent chance that today's patent covers technology built into the M1 processor to help it achieve its breakthrough performance. While the patent was published today, it was filed in Q4 2019 before the M1 surfaced.

Today, the U.S. Patent Office published a patent application from Apple titled "Multi-Mode Planar Engine for Neural Processor." Apple's invention relates to a circuit for performing operations related to neural networks, and more specifically to a neural processor that include a plurality of neural engine circuits and one or more multi-mode planar engine circuits.

An artificial neural network (ANN) is a computing system or model that uses a collection of connected nodes to process input data. The ANN is typically organized into layers where different layers perform different types of transformation on their input. Extensions or variants of ANN such as convolution neural network (CNN), recurrent neural networks (RNN) and deep belief networks (DBN) have come to receive much attention. These computing systems or models often involve extensive computing operations including multiplication and accumulation. For example, CNN is a class of machine learning technique that primarily uses convolution between input data and kernel data, which can be decomposed into multiplication and accumulation operations.

Depending on the types of input data and operations to be performed, these machine learning systems or models can be configured differently. Such varying configuration would include, for example, pre-processing operations, the number of channels in input data, kernel data to be used, non-linear function to be applied to convolution result, and applying of various post-processing operations. Using a central processing unit (CPU) and its main memory to instantiate and execute machine learning systems or models of various configuration is relatively easy because such systems or models can be instantiated with mere updates to code. However, relying solely on the CPU for various operations of these machine learning systems or models would consume significant bandwidth of a central processing unit (CPU) as well as increase the overall power consumption.

Apple's invention specifically relates to a neural processor that includes a plurality of neural engine circuits and a planar engine circuit operable in multiple modes and coupled to the plurality of neural engine circuits.

At least one of the neural engine circuits performs a convolution operation of first input data with one or more kernels to generate a first output. The planar engine circuit generates a second output from a second input data that corresponds to the first output or corresponds to a version of input data of the neural processor.

The input data of the neural processor may be data received from a source external to the neural processor, or outputs of the neural engine circuits or planar engine circuit in a previous cycle. In a pooling mode, the planar engine circuit reduces the spatial size of a version of second input data. In an elementwise mode, the planar engine circuit performs an elementwise operation on the second input data. In a reduction mode, the planar engine circuit reduces the rank of a tensor.

Apple's patent FIG. 3 below is a block diagram illustrating a neural processor circuit; FIGS. 6A, 6B, and 6C are conceptual diagrams respectively illustrating a pooling operation, an elementwise operation, and a reduction operation.

To review the deeper details, review Apple's patent application 20210103803.

Considering that this is a patent application, the timing of such a product to market is unknown at this time.

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One Thousand and One Talents: The Race for AI Dominance – Just Security

Introduction

The March 2016 defeat of Go world champion Lee Sedol by DeepMind, Alphabets artificially intelligent AlphaGo algorithm, will be remembered as a crucial turning point in the U.S.-China relationship. Oxfords Future of Humanity Institute branded the event Chinas Sputnik moment: a moment of realization among its political and military leaders that artificial intelligence (A.I.) could be Chinas key to achieving global hegemony and dominance over the United States.

Since then, Chinas government has plowed ahead in developing its A.I. capabilities, with President Xi Jinping calling for his country to become a world leader[1] as fast as possible. Given that A.I. technologies could contribute an estimated $112 billion to the Chinese economy by 2030[2], it is no surprise that Beijing believes A.I. to be a new focus of international competition.[3]

For the simple reason that China has focused on pragmatic, collaborative policies rather than restrictive, unilateral ones, it is currently on track to overtake the United States in the A.I. race. A.I.s potentially devastating military applications make the A.I. race not just a struggle for economic dominance, but also a national security threat for whichever State loses the advantage.

While the Biden administrations readiness to boost research and development (R&D) spending and reverse the previous administrations assault on U.S. alliances is a promising first step towards combating this technological challenge, much more is necessary to ensure that the United States technological capabilities do not fall behind those of rising powers.

To hold the line, the United States must leverage its historic alliances with Europe, Australia, and Southeast Asia to pool R&D funding into a multilateral A.I. research group. By creating incentives for scientists across the globe to collaborate together on U.S.-led A.I. development, the United States can ensure that its allies and partners maintain a technological edge over China long into the future.

A.I. Scare

In addition to its commercial benefits, the rapid development of A.I. will also advantage China by adding a potentially devastating tool to its cyberwar arsenal. Concerns about weaponized A.I. have recently been raised by the United Kingdoms Government Communications Headquarters. Their 2020 report claimed that military A.I. would facilitate the rapid adaptation of malware and require a speed of response far greater than human decision-making allows, thus making it difficult for countries to defend against it with current software. The conclusion that many experts have drawn is that the threat of A.I. cyberattacks necessitates the development of defensive A.I. by countries at risk of being targeted.

This threat is not merely theoretical; indeed, China has repeatedly indicated its intention to leverage new technologies like A.I. for offensive purposes. From a 2010 hack of Google by a group with ties to Chinas Peoples Liberation Army to a suspected cyberattack on Australian political institutions in 2020, it is clear that China will not shy away from utilizing the military applications of its emerging technologies.

In fact, Chinas 2017 Next Generation Artificial Intelligence Development Plan made this explicit. The report called for enhancing A.I. civil-military integration by establishing lines of communication and coordination between research institutions, private companies, and the military. Given that any future A.I. cyberattacks could be aimed at U.S. allies and interests, it is vital that the United States prioritizes the development of its own A.I. capabilities to defend against novel techniques.

Unfortunately, research shows that the United States is somewhat unprepared for incoming attacks. While China funneled an estimated $70 billion into A.I. in 2020 (up from $12 billion in 2017), the United States government devoted only $4.9 billiona quarter of what was allocated to the Chinese port of Tianjin for A.I. development alone. It was encouraging to see the Trump administration unveil its American A.I. initiative in response to Chinas 2017 plan albeit with a 19 month delay yet this was only a first step in the right direction. A multilateral strategy is also necessary to prevent China from overtaking the United States in a crucial sector which has the potential to tip the global balance of power.

The Xi Doctrine

The forward-leaning policies initiated by President Xi Jinping have led to many advancements, accelerating Chinas A.I. program and imperiling U.S. national security in the process. One of Xis most effective initiatives has been the so-called thousand talents plan, which offers high salaries and tempting benefits to scientists and researchers who agree to work with China on emerging technologies.[4] The plan has been enormously successful: a CIA official estimated that as many as 10,000 scientists from around the world have participated.

Its potential to grant China a strategic edge over the United States and its allies has also led the U.S. Senate to label the program a threat to American interests. Concerns center around the risk that U.S.-based scientists participating in the plan could transfer research achievements from American laboratories to Chinese ones, thereby accelerating Chinese A.I. development at the United States expense.

Instead of mitigating the issue, Trump era policy responses exacerbated Chinas lead by focusing on increasing A.I. export restrictions. In an attempt to prevent the outflow of sensitive military technologies to China and other hostile states, the U.S. Department of Commerce imposed restrictions on the exports of A.I. technologies. Far from giving the United States a competitive edge, the policy likely stymied A.I. investment by requiring businesses to obtain licenses, a requirement which elongates the export process and imposes high compliance costs on struggling startups. Proof of these policies damaging effects came in 2017 when, for the first time ever, Chinese A.I. startups received a greater share of global venture funding than U.S. startups received.

The Washington Pact

In order to improve U.S. A.I. policy, it is vital that the Biden administration understands two points. First, greater R&D spending is necessary to ensure that the United States can keep up with China on A.I. For the most part, the new administration has embraced this: Bidens campaign reiterated former Google CEO Eric Schmidts assertion that the United States must boost tech R&D because China is on track to surpass the U.S. in R&D. It even went on to claim that Chinas main reason for investing in new technologies was to overtake American technological primacy and dominate future industries.

Second, because American allies are themselves investing heavily into A.I., it is prudent to adopt multilateral solutions which leverage the United States historic alliances as opposed to unilateral America first responses. For instance, Germanys A.I. Made in Germany plan has allocated 3 billion to A.I. research over the next five years, while Frances A.I. for Humanity initiative has injected 1.5 billion into the sector. To balance against Chinas advancements, the United States should take advantage of these alliances and ensure that global investments go into developing A.I. capabilities across the broader liberal democratic sphere.

This second necessity does not appear to have received as much attention from the Biden administration so far. Despite its general recommitment to multilateralism through rejoining the Paris Climate Accord, reprioritizing NATO, and calling for a Summit for Democracy, the Biden administration has largely overlooked the idea of multilateral cooperation on A.I. research.

To match the Chinese technological challenge, the United States must establish research initiatives alongside its historic allies which will benefit U.S. A.I. development. This will have the effect of protecting U.S. national security long into the future by guaranteeing that the United States retains the edge over China in crucial A.I. innovations.

At the center of this policy should be an upgraded equivalent of Chinas thousand talents scheme that would be run as a joint initiative between America and its allies. The European Union, United Kingdom, Australia, and Japans determination to invest heavily into A.I., paired with their historic ties to the United States, suggests potential for large-scale multilateral research collaboration led by the United States.

The Biden administration should therefore suggest the foundation of a multilateral research programcall it One Thousand and One Talentswith the aim of attracting the best A.I. specialists from around the globe. Participating governments would funnel their annual A.I. budgets into the scheme in order to fund research projects with important military and commercial applications. The program would ensure that salaries would be directly competitive with Chinas thousand talents program and that incentives would be put in place to make the Western alternative more attractive than the Chinese one. Like NATO, U.S. leadership would be justified by its status as the main benefactor of the scheme.

The emphasis on multilateralism as a response to U.S.-Chinese competition should come as no surprise. As Princeton professor John Ikenberry writes, the key thing for U.S. leaders to remember when dealing with China is that it may be possible for China to overtake the United States alone, but it is much less likely that China will ever manage to overtake the Western order. It is no different with A.I.

Conclusion

The new technological challenges facing America call for a far-sighted and judicious foreign policy worthy of the worlds greatest superpower. While China may have the advantages of unrestricted State investment and well-planned incentive programs, it lacks alliances that run as deep as the NATO friendships the United States has long depended on. To overcome current Chinese advancements in A.I., the United States must unite with its partners around the world in order to increase the talent, funding, and skill available to it.

The proposed Thousand And One Talents research scheme would boost the United States competitiveness vis-a-vis China by pooling the resources of some of the wealthiest and most technologically advanced nations into U.S.-led A.I. development. Given the inevitability of Chinas rise, multilateral cooperation with like-minded democracies is the only way of ensuring that the U.S. does not face an existential security threat in the future.

The Biden administration must rise to the challenge by uniting with U.S. allies to compete with China on A.I. It is too risky to go it alone.

Editors Note:An earlier version of this essay received an honorable mention in New AmericasReshaping U.S. Security Policy for the COVID Eraessay competition.

[1] Quoted in Strittmatter, Kai, We Have Been Harmonized: Life in Chinas Surveillance State, p.165

[2] Ibid, p.166-167

[3] Quoted in Ibid, p.166-167

[4] Strittmatter, Kai, We Have Been Harmonized: Life in Chinas Surveillance State, p.171

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Is there intelligence in artificial intelligence? – Vaughan Today

This article was republished from France Conversation

Nearly 10 years ago, in 2012, the scientific world was amazed at the exploits of deep learning ( Deep learning). Three years later, this technology allowed AlphaGo to run Defeat the Go Champions. Some feared. Elon Musk, Stephen Hawking and Bill Gates were concerned about the approaching end of humanity, which would be replaced by an AI that would get out of control.

Wasnt that a bit of a stretch? This is exactly what the AI thinks. In an article he has Written in 2020 in a Watchman, GPT-3, this giant neural network of 175 billion parameters shows:

Im here to convince you not to worry. Artificial intelligence will not destroy humans. Trust me.

At the same time, we know that the power of the machines is constantly increasing. Training a network like GPT-3 was literally out of the question just five years ago. It is impossible to know what his successors could do in five, ten, or twenty years. If todays neural networks can replace dermatologists, why not replace us all?

Lets take the question back.

We immediately think of skills that involve our intuition or our creativity. No luck, Amnesty International claims to attack us in these areas as well. As proof of this, the fact that software-generated businesses have been sold quite expensive, some amounting to nearly half a million dollars. On the musical side, of course, everyone will have their own opinion, but we can actually recognize the accepted bluegrass or roughly Rachmaninoff in the MuseNet tradition created, like GPT-3, by OpenAI.

Will we soon have to surrender to the inevitable control of AI? Before calling for rebellion, lets try to see what we are dealing with. Artificial intelligence is based on several technologies, but its recent success is due to only one: neural networks, especially those of deep learning. However, a neural network is nothing more than a machine that can be linked. Deep web that She talked about it in 2012 Associated images: horse, boat, mushroom, with corresponding words. It is not enough to cry a genius.

However, this correlation mechanism has the somewhat miraculous characteristic of being persistent. You present a horse the network has never seen, it recognizes it as a horse. Youre adding noise to the image, dont disturb it. why ? Because the continuity of the process ensures that if the input to the network changes a little, its output will change a little as well. If the still hesitant network forced it to search for its best answer, it probably wouldnt change: the horse remains a horse, even if it differs from learned examples, even if the picture is noisy.

Good, but why do we say such associative behavior is smart? The answer seems clear: it can diagnose skin cancer, grant bank loans, keep the car on the road, detect diseases in physiological signals, etc. Thanks to their power to connect, these networks gain forms of experience that require years of study from humans. And when one of these skills, for example writing a newspaper article, appears to be holding on for some time, it suffices to make the machine swallow more examples, as happened with GPT-3, because the machine begins to produce convincing results.

Is it really to be smart? No. This kind of performance is only a small side of intelligence at best. What neural networks do is like rote learning. This is not, of course, because these networks constantly fill in the gaps between the examples they have been shown. Lets say it is almost by heart. Human experts, be they doctors, pilots or Go players, often dont do anything else when deciding reflexively, thanks to the sheer amount of examples learned during their training. But humans have many other powers.

The neural network cannot learn arithmetic. The correlation between processes such as 32 + 73 and their results has limitations. They can only reproduce the strategy of the mutt trying to guess the outcome, sometimes falling right. Too difficult account? How about an initial IQ test like: Continued Sequence 1223334444. Correlation by continuity does not always help to see the structure, N repeat N 5 times and continues with five 5. Are you still too difficult? The associations programs cant even guess that the animal that died on Tuesday is not alive on the Wednesday. why ? What are they missing?

Modeling in cognitive science has revealed the existence of several mechanisms, other than correlation by continuity, which are all components of human intelligence. Because their experience is prepared in advance, they cannot think of the right time to decide that the dead animal is still dead, or still Understand the meaning From the phrase he still hasnt died and the strangeness of this other sentence: He is not always dead. Their single digestion of large amounts of data does not allow them to do so Identify new structures Very obvious to us, like identical number sets in the sequence 1223334444. Their rote memorization strategy is also blind. Unpublished anomaly.

Detecting anomalies is an interesting case, because it is often through it that we measure the intelligence of others. The neural network will not see that the nose is missing from the face. Through continuity, he will continue to recognize the person, or perhaps confuse him with another. But he had no way of realizing that not having a nose in the middle of the face was an anomaly.

There are many other cognitive mechanisms inaccessible to neural networks. They are searching for their automation. It implements the operations performed at processing time, as neural networks simply perform the associations previously learned.

With a decade of hindsight Deep learning, The informed audience is starting to see neural networks as a super mechanism rather than as intelligence. For example, the press recently alerted to the astonishing performance of the DALL-E program, which produces creative images from verbal descriptions for example, the images that DALL-E imagines from the terms d-armchair. Lawyer, on the site OpenAI). We now hear far more thoughtful judgments than the cautionary reactions that followed the launch of AlphaGo: Its absolutely amazing, but we must not forget that this is an artificial neural network, trained to accomplish a task; there is neither creativity nor any form of intelligence. (Fabian) Chauvier, France Inter, January 31, 2021)

No form of intelligence? Lets not take too much, but lets stay clear about the huge divide separating neuron networks from what would be true AI.

Jean Louis Dessalles wrote Very Artificial Intelligence for the editions of Odile Jacob (2019). Lecturer, Institute of Mines Communication (IMT)

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Jordan Peterson – Wikipedia

Canadian clinical psychologist

Jordan Bernt Peterson (born 12 June 1962) is a Canadian professor of psychology at the University of Toronto, a clinical psychologist, and YouTube personality. He began to receive widespread attention in the late 2010s for his conservative views on cultural and political issues.[4][5][6]

Born and raised in Alberta, Peterson obtained bachelor's degrees in political science and psychology from the University of Alberta and a PhD in clinical psychology from McGill University. After teaching and research at Harvard University, he returned to Canada in 1998 to join the faculty of psychology at the University of Toronto. In 1999, he published his first book, Maps of Meaning: The Architecture of Belief, which became the basis for many of his subsequent lectures. The book combined information from psychology, mythology, religion, literature, philosophy, and neuroscience to analyze systems of belief and meaning.

In 2016, Peterson released a series of YouTube videos criticizing the Act to amend the Canadian Human Rights Act and the Criminal Code (Bill C-16), passed by the Parliament of Canada to introduce "gender identity and expression" as a prohibited grounds of discrimination.[a] He argued that the bill would make the use of certain gender pronouns into compelled speech, and related this argument to a general critique of political correctness and identity politics. He subsequently received significant media coverage, attracting both support and criticism.

Peterson's lectures and debatespropagated also through podcasts and YouTubegradually gathered millions of views. He put his clinical practice and teaching duties on hold by 2018, when he published his second book, 12 Rules for Life: An Antidote to Chaos. Promoted with a world tour, it became a bestseller in several countries. In 2021, Peterson published his third book, Beyond Order: 12 More Rules for Life.

Peterson was born on 12 June 1962, in Edmonton, Alberta,[7] and grew up in Fairview, a small town in the northwest of the province.[8] He was the eldest of three children born to Walter and Beverley Peterson. Beverley was a librarian at the Fairview campus of Grande Prairie Regional College, and Walter was a school teacher.[9][10] His middle name is Bernt (, BAIR-nt),[11] after his Norwegian great-grandfather.[12]

In junior high school, Peterson became friends with Rachel Notley and her family. Notley became leader of the Alberta New Democratic Party and 17th premier of Alberta.[13] Peterson joined the New Democratic Party (NDP) from ages 13 to 18.[14][15]

After graduating from Fairview High School in 1979, Peterson entered the Grande Prairie Regional College to study political science and English literature,[16] studying to be a corporate lawyer.[3] During this time he read Road to Wigan Pier by George Orwell which significantly affected his educational focus and worldview.[16][3] He later transferred to the University of Alberta, where he completed his B.A. in political science in 1982.[14] Afterwards, he took a year off to visit Europe, where he began studying the psychological origins of the Cold War; 20th-century European totalitarianism;[16][17] and the works of Carl Jung, Friedrich Nietzsche, Aleksandr Solzhenitsyn,[9] and Fyodor Dostoevsky.[17] He then returned to the University of Alberta and received a B.A. in psychology in 1984.[18] In 1985, he moved to Montreal to attend McGill University. He earned his Ph.D. in clinical psychology under the supervision of Robert O. Pihl in 1991, and remained as a post-doctoral fellow at McGill's Douglas Hospital until June 1993, working with Pihl and Maurice Dongier.[16][19]While at McGill University and the Douglas Hospital, he conducted research into familial alcoholism and its associated psychopathologies, such as childhood and adolescent aggression and hyperactive behavior.[20][21][22]

From July 1993 to June 1998,[1] Peterson lived in Arlington, Massachusetts, while teaching and conducting research at Harvard University, where he was hired as an assistant professor in the psychology department, later becoming an associate professor. During his time at Harvard, he studied aggression arising from drug and alcohol abuse[20] and showed great readiness to take on research projects, even unconventional ones.[14] Still while there, he switched his primary area of research from familial alcoholism to personality. After the change of focus, he has published extensively.[23][24][25][26][27][28] Two former PhD students, Shelley Carson, a psychologist and teacher from Harvard, and author Gregg Hurwitz, recalled that Peterson's lectures were already highly admired by the students.[29] He returned to Canada in July 1998 and eventually became a full professor at the University of Toronto.[1][18][30]

Peterson's areas of study and research within the fields of psychology are psychopharmacology,[31][32] abnormal,[33] neuro,[34] clinical, personality,[35][36] social,[36] industrial and organizational,[1] religious, ideological,[16] political, and creativity.[37] Peterson has authored or co-authored more than a hundred academic papers[38] and was cited almost 8,000 times as of mid-2017; at end of 2020 almost 15,000 times.[39][40]

Beginning 2003, Peterson has been sought by various mainstream and international TV productions for commentary on a wide range of subjects, from a personal- and social-psychological perspective. He was invited by Wodek Szemberg for appearances on Big Ideas in Canada as a lecturer.[41][42]A TV mini-series based on Maps of Meaning was aired on TVOntario in 2004.[18][42]In 2007, BBC Horizon produced Mad but Glad,[43] focussing on pianist Nick van Bloss; van Bloss met Peterson, who provided insights as a clinician and researcher with expertise on low-latent inhibition.[44][45]From 2011, TVOntario's The Agenda has featured Peterson as an essayist and panelist on psychologically relevant cultural issues.[46]

For most of his career, Peterson maintained a clinical practice, seeing about 20 people a week. He has been active on social media, and in September 2016 he released a series of videos in which he criticized Bill C-16.[13][47][48] As a result of new projects, he decided to put the clinical practice on hold in 2017[49] and temporarily stopped teaching as of 2018.[10][50] In February 2018, Peterson entered into a promise with the College of Psychologists of Ontario after a professional misconduct complaint about his communication and the boundaries he sets with his patients. The College did not consider a full disciplinary hearing necessary and accepted Peterson entering into a three-month undertaking to work on prioritizing his practice and improving his patient communications. Peterson had no prior disciplinary punishments or restrictions on his clinical practice.[51][52]

Regarding the topic of religion and God, Bret Weinstein moderated a debate between Peterson and Sam Harris at the Orpheum Theatre in Vancouver in June 2018. In July, the two debated the subject again, this time moderated by Douglas Murray, at the 3Arena in Dublin and The O2 Arena in London.[53][54] In April 2019, Peterson debated Slavoj iek at the Sony Centre in Toronto over happiness under capitalism versus Marxism.[55][56]

In 1999, Routledge published Maps of Meaning: The Architecture of Belief, in which Peterson describes a comprehensive theory about how people construct meaning, form beliefs, and make narratives. The book, which took Peterson 13 years to complete, draws concepts from various fields including mythology, religion, literature, philosophy, and psychology, in accordance to the modern scientific understanding of how the brain functions.[14][57][58][59][60][61]

According to Peterson, his main goal was to examine why individuals and groups alike participate in social conflict, exploring the reasoning and motivation individuals take to support their belief systems (i.e. ideological identification)[14] that eventually result in killing and pathological atrocities such as the Gulag, the Auschwitz concentration camp, and the Rwandan genocide.[14][60][61] Influenced by Jung's archetypal view of the collective unconscious in the book,[29] Peterson says that an "analysis of the world's religious ideas might allow us to describe our essential morality and eventually develop a universal system of morality."[61]

In 2004, a 13-part TV miniseries based on Peterson's book aired on TVOntario.[9][18][62]

In January 2018, Penguin Random House published Peterson's second book, 12 Rules for Life: An Antidote to Chaos, in which abstract ethical principles about life are provided in a more accessible style than his previous Maps of Meaning.[29][49][63] The book topped best-selling lists in Australia, Canada, France, Germany, the US, and the United Kingdom.[64][65][66]

To promote the book, Peterson embarked on a world tour.[67]

Peterson's third book, Beyond Order: 12 More Rules for Life, was released on 2 March 2021.[68] On 23 November 2020, his publisher Penguin Random House Canada (PRH Canada) held an internal town hall where many employees criticized the decision to publish the book.[69]

In 2013, Peterson registered a YouTube channel named JordanPetersonVideos,[70] and immediately began uploading recordings of lectures and interviews. Earliest dated recordings are from Harvard lectures, 1996. By the end of 2013, content on the channel included the lectures from Harvard, some interviews, and additional special lectures on two defining topics: "Tragedy vs Evil" and "Psychology as a career".

From 2014, uploads include recordings from two of his classes at University of Toronto ("Personality and Its Transformations" and "Maps of Meaning: The Architecture of Belief"),[71] special lectures ("Potential" for TEDx, "Death of the Oceans"), interviews, experiments in Q&A format, and video essays.

In March 2016, after three years of basic uploading of course videos, Peterson announced an interest to clean existing content and improve future content,[72] including a new experiment in crowdfunding through Patreon.[72]

The channel gathered more than 1.8 million subscribers and his videos received more than 65 million views as of August 2018.[48][73] By January 2021, subscribers on JordanPetersonVideos numbered at 3.4 million and total views reached over 200 million.[70]

From early 2017, funding for projects dramatically increased through his use of Patreon. Peterson hired a production team to film his 2017 psychology lectures at the University of Toronto. Donations received, range from $1,000 per month in August 2016 to $14,000 by January 2017; more than $50,000 by July 2017; and over $80,000 by May 2018.[13][48][74][75] With this funding, a number of projects and lecture series were proposed: more interviews, regular live Q&A sessions, public lecture series on the Bible (Genesis through Revelation), conversations with Muslims in Canada and US, and an online university. From May through December 2017, a lecture series on biblical stories was recorded and released on YouTube. A series of live Q&A events, appearing approximately monthly, were released beginning April 2017, through January 2018, then shifting to an irregular schedule through 2019. Regular donations for the YouTube channel were interrupted in January 2019, when Peterson deleted his Patreon account in public protest to the platform's controversial banning of another content creator.[76][77] Following this, Peterson and Dave Rubin announced the creation of a new, free speech-oriented social networking and crowdfunding platform.[78] This alternative had a limited release under the name Thinkspot later in 2019, and remained in beta testing as of December 2019.[79]

Peterson has appeared on many podcasts, conversational series, as well other online shows.[73][80] In December 2016, Peterson started The Jordan B. Peterson Podcast.[81] In March 2019, the podcast joined the Westwood One network with Peterson's daughter as a co-host on some episodes.[82] Peterson defended engineer James Damore after he was fired from Google for writing Google's Ideological Echo Chamber.[63]

In May 2017, Peterson began The Psychological Significance of the Biblical Stories,[83] a series of live theatre lectures, also published as podcasts, in which he analyzes archetypal narratives in Book of Genesis as patterns of behavior ostensibly vital for personal, social and cultural stability.[63] In October 2020, Peterson announced plans for a lecture series on the Book of Exodus and the Book of Proverbs.[84]

In March 2019, Peterson had his invitation of a visiting fellowship at Cambridge University rescinded. He had previously said the fellowship would give him "the opportunity to talk to religious experts of all types for a couple of months", and that the new lectures would have been on Book of Exodus.[85] A spokesperson for the University said there was "no place" for anyone who could not uphold the "inclusive environment" of the university.[86] After a week, Vice-Chancellor Stephen Toope explained that it was due to a photograph with a man wearing an Islamophobic shirt.[87] The Cambridge University Students' Union released a statement of relief, considering the invitation "a political act tolegitimise figures such as Peterson" and that his work and views are not "representative of the student body".[88] Peterson called the decision a "deeply unfortunate...error of judgement" and expressed regret that the Divinity Faculty had submitted to an "ill-informed, ignorant and ideologically-addled mob".[89][90]

In 2005, Peterson, with colleagues Daniel M. Higgins and Robert O. Pihl, established a website and company to deliver an evolving writing therapy system called The Self-Authoring Suite.[91] It consists of a series of online writing programs: the Past Authoring Program (a guided autobiography); two Present Authoring Programs, which aids analysis of personality faults and virtues; and the Future Authoring Program, which aids in developing a vision and planning desired futures.

To understand the statistical benefits of the suite academic trials have been conducted, and several studies published. Peterson states that more than 10,000 students have used the program.[9]

The Future Authoring program has been used with McGill University undergraduates on academic probation to improve grades, and since 2011 by the Rotterdam School of Management, Erasmus University.[92][93]

A 2015 study published by Palgrave Communications[b] showed a significant reduction in ethnic and gender-group differences in performance, especially among ethnic minority male students.[93][94] In 2020, the Higher Education Quality Council of Ontario (HEQCO) published a study[95] within its Access and Retention Consortium.[96] As HEQCO (with ARC) is an agency of Ontario government, this study represents published research for broader public awareness and application. To support this, several institutions were represented in the research: Mohawk College, University of Ottawa, University of Toronto, Queens University.[97] The program was tested at Mohawk College, and found similar results as with other studies.[c]

Peterson has characterized himself politically as a "classic British liberal",[17][98][99] and as a "traditionalist".[100] He has stated that he is commonly mistaken to be right-wing.[73] Yoram Hazony wrote in The Wall Street Journal that "[t]he startling success of his elevated arguments for the importance of order has made him the most significant conservative thinker to appear in the English-speaking world in a generation."[101] The New York Times described Peterson as "conservative-leaning",[102] while The Washington Post described him as "conservative".[103] Nathan J. Robinson of Current Affairs opines that Peterson has been seen "as everything from a fascist apologist to an Enlightenment liberal, because his vacuous words are a kind of Rorschach test onto which countless interpretations can be projected."[104]

Peterson's critiques of political correctness range over issues such as postmodernism, postmodern feminism, white privilege, cultural appropriation, and environmentalism.[80] His social media presence has magnified the impact of these views; Simona Chiose of The Globe and Mail wrote that "few University of Toronto professors in the humanities and social sciences have enjoyed the global name recognition Prof. Peterson has won."[48] Writing in the National Post, Chris Selley said that Peterson's opponents had "underestimated the fury being inspired by modern preoccupations like white privilege and cultural appropriation, and by the marginalization, shouting down or outright cancellation of other viewpoints in polite society's institutions",[105] while Tim Lott stated, in The Spectator, that Peterson became "an outspoken critic of mainstream academia".[17]

According to his studyconducted with one of his students, Christine Brophyof the relationship between political belief and personality, political correctness exists in two types: "PC-egalitarianism" and "PC-authoritarianism", which is a manifestation of "offense sensitivity".[106] Jason McBride claims that Peterson places classical liberals in the former, and so-called social justice warriors, who he says "weaponize compassion", in the latter.[9][16] The study also found an overlap between PC-authoritarians and right-wing authoritarians.[106]

Peterson suggests that universities are largely responsible for a wave of political correctness that has appeared in North America and Europe,[48] saying that he had watched the rise of political correctness on campuses since the early 1990s. Peterson believes the humanities have become corrupt and less reliant on science, in particular sociology. He contends that "proper culture" has been undermined by "post-modernism and neo-Marxism."[17]

Psychologist Daniel Burston has critiqued Peterson's views on academia. On Marxism, postmodernism, feminism, Burston faults Peterson's thought as oversimplified.[107] On the general state of academia, Burston generally agrees[108] with Peterson's criticisms of identity politics in academia,[111] as well as Peterson's charge that academia is "riddled with Left-wing bias and political correctness".[108] On summarizing the decline of the university, Burston disagrees with Peterson's critique against the Left, arguing that Peterson overlooks the degree to which the current decline of the humanities and social sciences are due to university administration focus.[108]

Peterson says that "disciplines like women's studies should be defunded", advising freshman students to avoid subjects like sociology, anthropology, English literature, ethnic studies, and racial studies, as well as other fields of study that he believes are corrupted by "post-modern neo-Marxists".[112][113][114] He believes these fields to propagate cult-like behaviour and safe-spaces, under the pretense of academic inquiry.[113][112] Peterson had proposed a website using artificial intelligence to identify ideologization in specific courses, but postponed the project in November 2017 as "it might add excessively to current polarization".[115][116]

He has repeatedly stated his opposition to identity politics, stating that it is practiced on both sides of the political divide: "[t]he left plays them on behalf of the oppressed, let's say, and the right tends to play them on behalf of nationalism and ethnic pride". He considers both "equally dangerous", saying that what should be emphasized, instead, is individual focus and personal responsibility.[117] He has also been prominent in the debate about cultural appropriation, stating that the concept promotes self-censorship in society and journalism.[118]

Peterson's perspectives on the influence of postmodernism on North American humanities departments have been compared to the Cultural Marxism conspiracy theory, including his use of "Cultural Marxism" and "postmodernism" as interchangeable terms and his take of postmodern philosophy as an offshoot or expression of "neo-Marxism".[64][119][120][121][122]

Several writers have associated Peterson with the so-called "intellectual dark web", including journalist Bari Weiss, who included Peterson in the 2018 New York Times article that first popularized the term.[123][124][125][126][127]

On 27 September 2016, Peterson released the first installment of a three-part lecture video series, entitled "Professor against political correctness: Part I: Fear and the Law".[13][128][47] In the video, he stated that he would not use the preferred gender pronouns of students and faculty, saying it fell under compelled speech, and announced his objection to the Canadian government's Bill C-16, which proposed to add "gender identity or expression" as a prohibited ground of discrimination under the Canadian Human Rights Act, and to similarly expand the definitions of promoting genocide and publicly inciting hatred in the hate speech laws in Canada.[a][129][128][130]

Peterson stated that his objection to the bill was based on potential free-speech implications if the Criminal Code were amended, claiming he could then be prosecuted under provincial human-rights laws if he refuses to call a transgender student or faculty member by the individual's preferred pronoun.[131][132] Furthermore, he argued that the new amendments, paired with section 46.3 of the Ontario Human Rights Code, would make it possible for employers and organizations to be subject to punishment under the code if any employee or associate says anything that can be construed "directly or indirectly" as offensive, "whether intentionally or unintentionally".[131] According to law professor Brenda Cossman and others, this interpretation of C-16 is mistaken, and the law does not criminalize misuse of pronouns,[132][133][134][135] though commercial litigator Jared Brown has described a scenario (albeit one he thinks unlikely) in which a person could end up in prison for contempt of court for persistently refusing to comply with a court order to refer to another person by their preferred gender pronouns.[136]

The series of videos drew criticism from transgender activists, faculty, and labour unions; critics accused Peterson of "helping to foster a climate for hate to thrive" and of "fundamentally mischaracterising" the law.[137][13] Protests erupted on campus, some including violence, and the controversy attracted international media attention.[138][139][140] When asked in September 2016 if he would comply with the request of a student to use a preferred pronoun, Peterson said "it would depend on how they asked me. If I could detect that there was a chip on their shoulder, or that they were [asking me] with political motives, then I would probably say no. If I could have a conversation like the one we're having now, I could probably meet them on an equal level."[140] Two months later, the National Post published an op-ed by Peterson in which he elaborated on his opposition to the bill, saying that gender-neutral singular pronouns were "at the vanguard of a post-modern, radical leftist ideology that I detest, and which is, in my professional opinion, frighteningly similar to the Marxist doctrines that killed at least 100 million people in the 20th century."[141]

In response to the controversy, academic administrators at the University of Toronto sent Peterson two letters of warning, one noting that free speech had to be made in accordance with human rights legislation, and the other adding that his refusal to use the preferred personal pronouns of students and faculty upon request could constitute discrimination. Peterson speculated that these warning letters were leading up to formal disciplinary action against him, but in December the university assured him he would retain his professorship, and in January 2017 he returned to teach his psychology class at the University of Toronto.[13][142]

In February 2017, Maxime Bernier, candidate for leader of the Conservative Party of Canada, stated that he had shifted his position on Bill C-16, from support to opposition, after meeting with Peterson and discussing it.[143] Peterson's analysis of the bill was also frequently cited by senators who were opposed to its passage.[144] In April 2017, Peterson was denied a Social Sciences and Humanities Research Council (SSHRC) grant for the first time in his career, which he interpreted as retaliation for his statements regarding Bill C-16.[39] However, a media-relations adviser for SSHRC said, "Committees assess only the information contained in the application."[145] In response, Rebel News launched an Indiegogo crowdfunding campaign on Peterson's behalf,[146] raising C$195,000 by its end on 6 May, equivalent to over two years of research funding.[147] In May 2017, as one of 24 witnesses who were invited to speak about the bill, Peterson spoke against Bill C-16 at a Canadian Senate Committee on Legal and Constitutional Affairs hearing.[144]

In November 2017, Lindsay Shepherd, the teaching assistant of a Wilfrid Laurier University first-year communications course, was censured by her professors for showing, during a classroom discussion about pronouns, a segment of The Agenda in which Peterson debates Bill C-16 with another professor.[148][149][150] The reasons given for the censure included the clip creating a "toxic climate", being compared to a "speech by Hitler",[15] and being itself in violation of Bill C-16.[151] The censure was later withdrawn and both the professors and the university formally apologized.[152][153][154] The events were cited by Peterson, as well as several newspaper editorial boards[155][156][157] and national newspaper columnists,[158][159][160][161] as illustrative of the suppression of free speech on university campuses. In June 2018, Peterson filed a $1.5-million lawsuit against Wilfrid Laurier University, arguing that three staff members of the university had maliciously defamed him by making negative comments about him behind closed doors.[162] As of September2018,[update] Wilfrid Laurier had asked the court to dismiss the lawsuit, saying it was ironic for a purported advocate of free speech to attempt to curtail free speech.[163]

Peterson has argued that there is an ongoing "crisis of masculinity" and "backlash against masculinity" in which the "masculine spirit is under assault."[8][164][165][166] He has argued that the left characterises the existing societal hierarchy as an "oppressive patriarchy" but "dont want to admit that the current hierarchy might be predicated on competence."[8] He has said men without partners are likely to become violent, and has noted that male violence is reduced in societies in which monogamy is a social norm.[8][164] He has attributed the rise of Donald Trump and far-right European politicians to what he says is a negative reaction to a push to "feminize" men, saying "If men are pushed too hard to feminize they will become more and more interested in harsh, fascist political ideology."[167] He attracted considerable attention over a 2018 Channel 4 interview in which he clashed with interviewer Cathy Newman on the topic of the gender pay gap.[168][169] He disputed the contention that the disparity was solely due to sexual discrimination.[169][170][171]

Jordan Peterson has favourable views on the teachings of the Orthodox Church.[172][173] However, Eastern Orthodox artist Jonathan Pageau who has worked with Peterson in several dialogues about art, beauty and faith (including the "Logos" forum in Toronto) claims that Peterson is not a Christian ("He has flirted with that, but pulled back").[174]

In a 2017 interview, Peterson was asked if he was a Christian; he responded, "I suppose the most straight-forward answer to that is yes."[175] When asked if he believes in God, Peterson responded: "I think the proper response to that is No, but I'm afraid He might exist."[49] Writing for The Spectator, Tim Lott said Peterson draws inspiration from Jung's philosophy of religion and holds views similar to the Christian existentialism of Sren Kierkegaard and Paul Tillich. Lott also said that Peterson has respect for Taoism, as it views nature as a struggle between order and chaos and posits life would be meaningless without this duality.[17]

Writing in Psychoanalysis, Politics and the Postmodern University, Daniel Burston argues that Petersons views on religion reflect a preoccupation with what Tillich calls the vertical or transcendent dimension of religious experience but demonstrate little or no familiarity with (or sympathy for) what Tillich termed the horizontal dimension of faith, which demands social justice in the tradition of the Biblical Prophets.[176]

In his video posted on October 2020, Peterson mentioned, "...with God's grace and mercy I'll be able to start generating original material once again and pick up where I left off." [177]

Peterson married Tammy Roberts in 1989;[13] the couple have a daughter, Mikhaila, and a son, Julian.[9][13]

Following Peterson's rise to fame, his daughter Mikhaila has built an online following herself and offers dietary advice of only eating meat.[178][179]

Starting around 2000, Peterson began collecting Soviet-era paintings.[15] The paintings are displayed in his house as a reminder of the relationship between totalitarian propaganda and art, and as examples of how idealistic visions can become totalitarian oppression and horror.[29][50] In 2016, Peterson became an honorary member of the extended family of Charles Joseph, a Kwakwakawakw artist, and was given the name Alestalagie ('Great Seeker').[15][180]

In 2016, Peterson had a severe autoimmune reaction to food and was prescribed clonazepam.[181] In late 2016, he went on a strict diet consisting only of meat and some vegetables, in an attempt to control his severe depression and the effects of an autoimmune disorder including psoriasis and uveitis.[10][100] In mid-2018, he stopped eating vegetables, and continued eating only beef (carnivore diet).[182]

In April 2019, his prescribed dosage of clonazepam was increased to deal with the anxiety he was experiencing as a result of his wife's cancer diagnosis.[183][184][185] Starting several months later, he made various attempts to lessen his intake, or stop taking the drug altogether, but experienced "horrific" benzodiazepine withdrawal syndrome, including akathisia,[186] described by his daughter as "incredible, endless, irresistible restlessness, bordering on panic".[187][183] According to his daughter, Peterson and his family were unable to find doctors in North America who were willing to accommodate their treatment desires, so in January 2020, Peterson, his daughter and her husband flew to Moscow, Russia for treatment.[188] Doctors there diagnosed Peterson with pneumonia in both lungs upon arrival, and he was put into a medically induced coma for eight days. Peterson spent four weeks in the intensive care unit, during which time he allegedly exhibited a temporary loss of motor skills.[183][189]

Several months after his treatment in Russia, Peterson and his family moved to Belgrade, Serbia for further treatment.[181] In June 2020, Peterson made his first public appearance in over a year, when he appeared on his daughter's podcast, recorded in Belgrade.[181] He said that he was "back to my regular self", other than feeling fatigue, and was cautiously optimistic about his prospects.[181] He also said that he wanted to warn people about the dangers of long-term use of benzodiazepines (the class of drugs that includes clonazepam).[181] In August 2020, his daughter announced that her father had contracted COVID-19 during his hospital stay in Serbia.[190] Two months later, Peterson posted a YouTube video to inform that he had returned home and aimed to resume work in the near future.[84]

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How Jordan Peterson Broke His Most Important Rule (For Life)

Jordan Peterson. (Photo by Chris Williamson/Getty Images)

Its genuinely tragic what happened to Jordan Peterson.

The Canadian psychology professor first rose to fame by railing against the liberal obsession with identity that shaped the culture wars of 2016, and subsequently became so polarizing (and popular) that his self-help book, 12 Rules For Life, sold over three million copies worldwide.

Peterson offered solid advice for angry, isolated young men; he promoted the idea of personal responsibility, discipline and self-confidence. The problem was that his positive messaging was often accompanied by his other beliefs, some of which were simply old-fashioned conservative ideals, repackaged, and some were really quite strange. Harmful, even.

Despite marketing himself as an intellectual who wasnt afraid to ask tough questions, Peterson would often blurt out seriously unscientific and outlandish claims, most famously, his strange fixation on lobsters, and the supposed similarity between crustaceans and humankind, which he used to justify the existence of unjust hierarchies.

Its a bit like pointing to a bee hive, and claiming that the insect's success makes a compelling argument to restore the monarchy.

Eventually, Peterson started to hang out with race realist Stefan Molyneux (so much for rejecting identity politics) and began to promote his daughters eye-wateringly stupid diet, which consists solely of beef, salt and water (sounds like a great way to develop scurvy).

Months into his all-beef diet, Peterson claimed that ingesting any substance other than beef would cause him serious psychological and physical harm; he even claimed that a single glass of apple cider caused him to stay awake for a full month, and filled him with an overwhelming sense of impending doom (Im not kidding).

Peterson ended up becoming addicted to anti-anxiety medication after personal tragedy struck, and suffered all sorts of horrendous health complications - its still not clear if he ever really recovered.

Now, Peterson is back, and he is about to release another self-help book, titled, Beyond Order: 12 More Rules for Life. Which seems incredibly hypocritical, considering his big rule, one that he consistently touted while public speaking, which reads:

"Set your house in perfect order before you criticize the world."

This rule always bothered me, a lot. Its the kind of thing that sounds innocuous on the surface - after all, whats wrong with practicing what you preach? Surely, there are plenty of obnoxious activists who could use that advice.

But the way Peterson promoted this rule wasnt meant to encourage - he was essentially telling activists to be quiet, to accept the worlds structural injustices, because they were imperfect and didnt clean their rooms, or whatever.

That rule functions as a cudgel, to crush the idealism of young people. And its a rule that has no basis in reality - historical heroes like Gandhi, Nelson Mandela and Martin Luther King Jr. had plenty of personal problems too.

And so, quite frankly, does Peterson.

Ironically, having a messy personal life doesnt mean that Petersons emphasis on personal improvement, on finding meaning through responsibility, isnt worth listening to. That is undeniably good advice.

But the notion that only those with neat and tidy personal lives are allowed to criticize the world, is dangerous nonsense.

Just like the idea of a human living solely on beef, salt, and water.

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How Jordan Peterson Broke His Most Important Rule (For Life)

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Jordan Peterson: Ta-Nehisi Coates’ ‘Captain America …

Jordan Peterson, the conservative psychology professor and podcast host, has claimed on Twitter that hes inspired the villain Red Skull featured in Ta-Nehisi Coates run of Captain America comics.

In Captain America Volume 9 #28, which was released by Marvel Comics on March 31, Red Skull preaches his Ten Rules for Life as well as Chaos and Order and The Feminist Trap. This appears to reference Petersons self-help book 12 Rules for Life: An Antidote to Chaos released in 2018, and Petersons contention that chaos is represented by the feminine.

Late on Monday, Peterson posted screenshots of the Captain American issue, asking his followers to verify his suspicion that he was the inspiration for Red Skull in its story.

Do I really live in a universe where Ta-Nehisi Coates has written a Captain America comic featuring a parody of my ideas as part of the philosophy of the arch villain Red Skull? he tweeted. He currently has the tweet pinned on his profile.

A representative for Marvel Comics did not respond to a request fromVariety to comment.

The main theme of the issue alludes to internet influences who use their platforms to radicalize young men online in order to fuel reactionary fires and their own agendas.

What has happened to the men of the world is truly one of the great tragedies of our time. Once, the American man was a conqueror. Now he is but a caretaker, Skull says in one of his online speeches. No more shall women be summoned to fight your battles. I offer steel for your spine and iron for your gut. I offer you the sword of manhood.

Captain America mentions a young boy disappearing into the internet, emerging with a new theory of the world fed to him by Red Skull what appears to be another reference to followers of Petersons who have taken to his philosophy largely through his YouTube channel.

[Skull] tells them what theyve always longed to hear, Cap says. That they are secretly great. That the whole worlds against them. That if theyre truly men, theyll fight back. And bingo. Thats their purpose. Thats what they live for and thats what theyll die for.

Coates issue eludes to other issues that are currently roiling the US. One page depicts a divided rally, with one sides picket signs reading America Forever! while the others read Equality Now and Stop Hate Now. At the end of the issue, Sharon Carter is tending to Captain Americas wounds, while telling him about how the Power Elite, a Hydra-based group inspired by Red Skull, is trying to attack the idea of America, and references attacks at the US Capitol.

Coates is an influential best-selling writer who came to prominence first with a 2014 reported essay in The Atlantic titled The Case for Reparations, followed by his 2015 book Between the World and Me. Hes also written Black Panther comics for Marvel, and started his current run on Captain America in 2018.

In February, Warner Bros. tapped Coates to write the script for a new Superman film with J.J. Abrams Bad Robot.

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