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Taking the mainframe into the cloud – ITWeb

Kevin Kemp, business development manager: application modernisation and connectivity, Micro Focus.

As enterprises increasingly move to the cloud, it is important for business leaders to understand that mainframes, which have for many years been the backbone of the global financial system, can also be accessed from any computing platform.

This, explains Kevin Kemp, business development manager for application modernisation and connectivity at Micro Focus, allows for the development and deployment of the latest, cloud-ready applications while still enabling the business to derive value from heritage investments. This not only results in more efficient and cost-effective ways to implement new initiatives, but should also significantly improve the customer, supply chain and employee experience.

It is worth noting that the majority of large banks, for example, still run significant mainframe estates. There are obviously good reasons for this, including the mainframes capability to process information, its ability to handle large workloads and process these against tight deadlines, and the strong security within the mainframe architecture, he explains.

Remember that compared to the more complex, server-based architectures, the mainframe one is much simpler and therefore lacks many of the vulnerabilities found in the more complicated architectures.

Kemp notes that mainframes today still process the vast majority of credit card and other financial transactions globally, as well as handling the majority of production IT workloads, adding that this is because they are more secure and more cost efficient than other computing platforms.

Justin Agar, account executive for application modernisation and connectivity at Micro Focus.

Justin Agar, account executive for application modernisation and connectivity at Micro Focus, suggests that decision-makers should consider accessing the mainframe from the cloud in the same manner they consider moving desktop applications to the cloud.

If you think about it, moving employees from a desktop version of Microsoft Office to the cloud-based Office 365 enables users to do the same work, only more efficiently. If this is the case, it should be clear that moving the host or mainframe access from the desktop to the cloud will enable mainframe users to do the same work they were doing before, but more efficiently. Nothing changes on the mainframe only the platform from which it is accessed, he says.

Remember too that the mainframe has much higher computing power than most commodity servers. Thus, you are able to maximise its ability to compute effectively, while at the same time ensuring you only use this compute power for the toughest and most essential work, while shifting all the non-essential work to the cloud for processing.

He notes that one of the key reasons for adopting such an approach is that the ability to shift compute power between the cloud and the mainframe gives the business owners the ability to manage their costs far better.

Kemp adds that the flexibility this offers in respect of managing workloads more effectively is critical, as cloud also offers the ability to scale up or down in real-time, unlike mainframes, which is why it is important to save the mainframe for the most essential work only.

While each environment is different, we have worked with clients who have budgets in excess of R300 million per annum, and combining the mainframe and cloud environments in this manner has reduced the costs associated with a pure mainframe environment by around 30%.

Recent research shows that modernisation must be continuous and evolving in order to meet the changing needs of todays business climate. Digital transformation demands a flexible and adaptive strategy aimed at improving results and accelerating time to value. By clicking here, IT leaders can quickly map their current IT estate to their future business strategy all while finding the right balance between costs, risk and speed.

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I beheld a quantum computer. It was weird and excellent. – Stuff

IBM

IBM scientist Andreas Fuhrer looks at the cryogenic refrigerator which keeps a quantum computers qubits super cold.

Peter Griffin is a freelance science and technology writer. He was the founding director of the Science Media Centre and founding editor of Sciblogs.co.nz

OPINION: You have to hand it to the likes of Niels Bohr, Werner Heisenberg and Erwin Schrdinger, scientists who were instrumental in developing the field of quantum mechanics about 100 years ago.

They had their work cut out for them trying to explain to a sceptical public the forces that dictate how the world works on the atomic and subatomic scale.

Even Albert Einstein whose own discoveries were towering reference points for these scientists could never reconcile that quantum measurements and observations are fundamentally random.

"It is this view against which my instinct revolts," he wrote in 1945.

READ MORE:* What does Google's Quantum Supremacy actually mean?* World-first experiment introducing atoms to one another may be key to next 'quantum revolution'* Quantum computer a possibility in 10 years* The ultimate geek pilgrimage* A computer 100m times faster than yours

Weve learned much about quantum mechanics since then, including how the principles of superposition and entanglement explain how information can be processed in ways computers like our laptops and smartphones cant match.

Last week I stood for the first time in front of a fully functioning quantum computer, IBMs Quantum System One, at the companys research labs in Yorktown Heights, New York.

The machine looks like a beautiful gold chandelier shrouded in a metal case that creates a vacuum in which the whole device is chilled to just above absolute zero, as cold as outer space.

The highly controlled conditions are required to eliminate interference that could prevent the quantum chip at the tip of the chandelier from doing its thing, which is to activate qubits the quantum version of the bits, the digital ones and zeros our binary computers work with.

IBM, Google, Microsoft and numerous other companies and research institutions have demonstrated how quantum computers are very good at a narrow range of computational tasks, such as simulating nature. Thats already seen them put to work modelling molecules and in the complex field of materials science.

ROBERT KITCHIN/Stuff

Stuff science columnist Peter Griffin.

Programmers are now working on computer algorithms to expand the ways in which quantum computers can be used. Cryptography experts think large quantum computers could crack existing encryption systems, which would cause a cybersecurity nightmare.

But quantum computers will need to scale up massively in power and be less prone to errors to be useful more broadly. IBM last year produced Eagle, a 127-qubit processor for its quantum computer and plans to introduce Osprey, its 433-qubit chip this year.

Eventually machines with hundreds of thousands or millions of qubits could be available for number crunching on a scale weve never seen before.

It's unlikely youll ever have a quantum computer on your desk or in your garage. Instead, IBM and its rivals rent access to their quantum computers as a cloud computing service.

Todays regular computers arent heading for the dustbin either. They are better at a wide range of tasks and can work in tandem to make quantum computers more useful.

Its unclear whether quantum computing can be properly applied to solving the big problems facing the world new antibiotics or climate change.

But the blistering pace of technical progress suggests it's a field heating up and one worth watching.

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Cloud Computing in Higher Education Market Share 2022 Size, Industry Revenue, Growth Insights, Top Players, Recent Developments, and Forecast till…

The study undertaken by Astute Analytica foresees a tremendous growth in revenue of the market forglobal cloud computing in higher education marketfromUS$ 2,693.5 Millionin 2021 toUS$ 15,180.1 Millionby 2030. The market is anticipated to grow at a CAGR of 22% during the forecast period 2022-2030.

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Cloud computing in higher education provides an online platform for educational institutes through various applications and subscription models. In this era of technology, employing latest IT technologies and services in higher education assists teachers, administrators and students in their education related activities. Cloud computing in higher education centrally manages the various business processes such as student and course management, helps teachers in uploading learning materials, students to access their homework, administrators to easily collaborate with each other and library management among others.Cloud computing segment is gaining majority of the spenders from high income group as well as skilled share of people from around the world.

On the basis of institute type, thetechnical schools are estimated to hold the highest market share in 2021 and is also expected to project the highest CAGR over the forecast period owing to increasing demand for cloud computing in technical schools.Moreover, based on ownership,private institutes segment is anticipated to hold the largest market share owing to increasing funding in private institutes for adoption of cloud computing services. Whereas, the public institutes segment is expected to grow at the highest CAGR over forecast period. Furthermore, in terms of application, administration application holds a major share in the cloud computing in higher education in 2021. Whereas, unified communication is expected to project the highest CAGR over the forecast period due to increasing trend of e-learning. In addition to this, by deployment, the hybrid cloud segment held the largest market share in 2021.

Market Dynamics and Trends

Drivers

The increasing adoption of SaaS based cloud platforms in higher education, increasing adoption of e-learning, increasing IT spending on cloud infrastructure in educationand increasingapplication of quantum computing in education sectorwill boost the global cloud computing in higher education market during the forecast period. Software-as-a-Service (SaaS) is a type of delivery model of cloud computing. In the higher education sector, SaaS applications include hosting various management systems for educational institutes and managing other activities. Moreover, higher education industry witnesses an increased adoption of e-learning due to its easy accessibility and high effectiveness. Users such as drop-outs, transfer learners, full-time employees are increasingly relying on e-learning trainings and education to upgrade their skills. Furthermore, higher education institutes are rapidly moving towards cloud-based services to save an intensive IT infrastructure cost and boost efficiency of operations.

Restraints

Cybersecurity and data protection risks, lack of compliance to the SLAand legal and jurisdiction issues is a restraining factor which inhibits the growth of the market during the forecast period. Issues related to data privacy pose threats in interest to mitigation of higher education institutions to the cloud. There are federal regulations for higher education institutes along with state and local laws to manage information security in the education environment. Moreover, the level of complexity in the cloud is high, which usually complies with several service providers and thus makes it hard for users to make changes or intervene. Also, the cloud computing industry faces various legal and jurisdiction issues that can run into years due to regional laws.

Cloud Computing in Higher Education Market Country Wise Insights

North AmericaCloud Computing in Higher EducationMarket-

US holds the major share in terms of revenue in theNorth Americacloud computing in higher education market in 2021 and is also projected to grow with the highest CAGR during the forecast period. Moreover, in terms of institute type, technical schools hold the largest market share in 2021.

EuropeCloud Computing in Higher EducationMarket-

Western Europeis expected to project the highest CAGR in theEuropecloud computing in higher education market during forecast period. Wherein,Germanyheld the major share in theEuropemarket in 2021 because there is high focus on innovations obtained from research & development and technology adoption in the region.

Asia PacificCloud Computing in Higher EducationMarket-

Indiais the highest share holder region in theAsia Pacificcloud computing in higher education market in 2021and is expected to project the highest CAGR during the forecast period owing to potential growth opportunities, as end users such as schools and universities are turning toward cloud services in order to offer high quality services that help users to collaborate, share and track multiple versions of a document.

South AmericaCloud Computing in Higher EducationMarket-

Brazilis projected to grow with the highest CAGR in theSouth Americacloud computing in higher education market over the forecast period. Furthermore, based on ownership, private institutes segment holds the major share in 2021 in theSouth Americacloud computing in higher education market owing to increasing funding in private institutes for adoption of cloud computing services.

Middle EastCloud Computing in Higher EducationMarket-

Egyptis the highest share holder region in 2021 and UAE is projected to grow with the highest CAGR during the forecast period. Moreover, in terms of application, administration holds a major share in the cloud computing in higher education in 2021. Whereas, unified communication is expected to project the highest CAGR over the forecast period due to increasing trend of e-learning.

AfricaCloud Computing in Higher EducationMarket-

South Africais the highest share holder region in theAfricacloud computing in higher education market in 2021. Furthermore, by deployment, the private cloud segment is expected to witness the highest CAGR during forecast period due to the security benefits provided by the private deployment of the cloud.

Competitive Insights

GlobalCloud Computing in Higher Education Market is highly competitive in order to increase their presence in the marketplace. Some of the key players operating in the global cloud computing in higher education market include Dell EMC, Oracle Corporation, Adobe, Inc., Cisco Systems, Inc., NEC Corporation, Microsoft Corporation, IBM Corporation, Salesforce.com, Netapp, Ellucian Company L.P., Vmware, Inc and Alibaba Group among others.

Segmentation Overview

Global Cloud Computing in Higher Education Market is segmented based on institute type, ownership, application, deployment and region. The industry trends in the global cloud computing in higher education market are sub-divided into different categories in order to get a holistic view of the global marketplace.

Following are the different segments of the Global Cloud Computing in Higher Education Market:

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By Institute Type segment of the Global Cloud Computing in Higher Education Market is sub-segmented into:

By Ownership segment of the Global Cloud Computing in Higher Education Market is sub-segmented into:

By Application segment of the Global Cloud Computing in Higher Education Market is sub-segmented into:

By Deployment segment of the Global Cloud Computing in Higher Education Market is sub-segmented into:

By Region segment of the Global Cloud Computing in Higher Education Market is sub-segmented into:

North America

Europe

Western Europe

Eastern Europe

Asia Pacific

South America

Middle East

Africa

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About Astute Analytica

Astute Analytica is a global analytics and advisory company which has built a solid reputation in a short period, thanks to the tangible outcomes we have delivered to our clients. We pride ourselves in generating unparalleled, in depth and uncannily accurate estimates and projections for our very demanding clients spread across different verticals. We have a long list of satisfied and repeat clients from a wide spectrum including technology, healthcare, chemicals, semiconductors, FMCG, and many more. These happy customers come to us from all across the Globe. They are able to make well calibrated decisions and leverage highly lucrative opportunities while surmounting the fierce challenges all because we analyze for them the complex business environment, segment wise existing and emerging possibilities, technology formations, growth estimates, and even the strategic choices available. In short, a complete package. All this is possible because we have a highly qualified, competent, and experienced team of professionals comprising of business analysts, economists, consultants, and technology experts. In our list of priorities, you-our patron-come at the top. You can be sure of best cost-effective, value-added package from us, should you decide to engage with us.

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Light Reading VS Deep Reading: What You Read Matters … – Learning Mind

As information becomes more and more web-based, so too does the attention of the younger generations.

We rely on the internet to give us everything, from news to research, and it is having a huge impact on what we read and how we read it.

We have moved away from the deep reading of different texts and journals and moved towards the skim, light reading of web posts, and websites in order to get the information that we want.

This affects the way that our brains process and relay information.Instead of taking in each element of the text we read, we simply find the pieces of information that serve our agendas, rather than developing our brains to help us recall the information later.

When we read deeply, we read much slower; we take in the details of different sensory descriptions and we become much more immersed in the things we read.

Whereas with thelight reading, we read much faster, we look for the pieces of information that we want and we dont really look at everything else around it. This doesnt give us all of the information available from the text and it doesnt exercise our brains as much as deeper reading does.

Deep reading activates the centres in your brain which are responsible for speech, hearing, and vision, and helps them to work together to create an image in our heads.

Reading in this way also develops our ability to perceive and use language, and gives us the greater ability to create more complex sentence structures and fuller descriptions.

When we read deeply, we also take in the information much better than in the case of light reading. The information is stored in the brain when we deep read and is ready to be recalled later on.

Deep reading has also been shown to make us nicer. As we read we can articulate and develop the skill to understand our emotions much better than before, and this helps us to understand emotions in others as well.

Reading things such as poems, novels, and academic reports can massively develop your writing abilities. Make sure to take your time and soak in all of the available information to create a full picture, rather than skim-reading the information.

Putthese types of writings in your life rather than getting information only from online blogs and televisions shows, as they make your brain switch off almost immediately. Even though they are entertaining, they wont develop your writing ability whatsoever.

Unfortunately, in the modern world, reading has become an unpopular pastime, but the benefits of real reading are massive and shouldnt be ignored.

Next time youre writing a paper, a short story, or even just have some free time, take some time to read and read deeply, taking in all the information and really enjoying it.

References:

Contributing writer at Learning Mind

Francesca Forsythe is a professional writer who holds a dual award Master's degree in European Law and Philosophy of Law from Leiden University. She has written for several websites on a range of subjects across lifestyle, relationships, and health & fitness, as well as academic pieces in her fields of study.

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Light Reading VS Deep Reading: What You Read Matters ... - Learning Mind

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The hype around DeepMinds new AI model misses whats actually cool about it – MIT Technology Review

Nature is trying to tell us something here, which is this doesnt really work, but the field is so believing its own press clippings that it just cant see that, he adds.

Even de Freitass DeepMind colleagues Jackie Kay and Scott Reed, who worked with him on Gato, were more circumspect when I asked them directly about his claims. When asked whether Gato was heading toward AGI, they wouldnt be drawn. I dont actually think its really feasible to make predictions with these kinds of things. I try to avoid that. Its like predicting the stock market, said Kay.

Reed said the question was a difficult one: I think most machine-learning people will studiously avoid answering. Very hard to predict, but, you know, hopefully we get there someday.

In a way, the fact that DeepMind called Gato a generalist might have made it a victim of the AI sectors excessive hype around AGI. The AI systems of today are called narrow, meaning they can only do a specific, restricted set of tasks such as generate text.

Some technologists, including some at DeepMind, think that one day humans will develop broader AI systems that will be able to function as well as or even better than humans. Though some call this artificial general intelligence, others say it is like "belief in magic. Many top researchers, such as Metas chief AI scientist Yann LeCun, question whether it is even possible at all.

Gato is a generalist in the sense that it can do many different things at the same time. But that is a world apart from a general AI that can meaningfully adapt to new tasks that are different from what the model was trained on, says MITs Andreas: Were still quite far from being able to do that.

Making models bigger will also not address the issue that models dont have lifelong learning, which would mean that if taught something once, they would understand all the implications and use it to inform all the other decisions they make, he says.

The hype around tools like Gato is harmful for the general development of AI, argues Emmanuel Kahembwe, an AI and robotics researcher and part of the Black in AI organization cofounded by Timnit Gebru. There are many interesting topics that are left to the side, that are underfunded, that deserve more attention, but thats not what the big tech companies and the bulk of researchers in such tech companies are interested in, he says.

Tech companies ought to take a step back and take stock of why they are building what they are building, says Vilas Dhar, president of the Patrick J. McGovern Foundation, a charity that funds AI projects for good.

AGI speaks to something deeply humanthe idea that we can become more than we are, by building tools that propel us to greatness, he says. And thats really nice, except it also is a way to distract us from the fact that we have real problems that face us today that we should be trying to address using AI.

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DNAStar Beefs up Protein Structure Prediction With DeepMind-Powered NovaFold AI – GenomeWeb

CHICAGO This month, DNAStar formally launched NovaFold AI, an update to its NovaFoldprotein structure prediction software that incorporates the AlphaFold2 artificial intelligence system from Google sister company DeepMind Technologies. The company had introduced a beta version of the product, dubbed NovaFold AI powered by AlphaFold2, in February.

Steve Darnell, team leader of DNAStar's structural biology and protein team, called NovaFold AI a cloud version of the AlphaFold 2 pipeline. The offering lets usersaccess the AlphaFold protein structure prediction method from within DNAStar'sNovaCloud Services interface of the firm's Protean 3D visualizationand analysis suite.

He said that AlphaFold 2 is designed to help researchers without a bioinformatics background predict structures.

"This release allows customers to more tightly integrate the analysis with running the prediction," added DNAStar General Manager Shawn Grass.

Madison, Wisconsin-based DNAStar sees NovaFold AI as a growth opportunity.

"The structure market has been a little more challenging for us to get into, because when people think of us, they think of just DNA. They don't think of us in the protein area," Grass said. "Our hope is with the excitement and buzz right now about structure prediction that this will give us an opportunity to expand our reach."

DNAStar, which has been in business since 1984, is actually quite active beyond DNA.

Last year, the privately held firm introduced version 17.3 of its Lasergene software for DNA, RNA, and protein sequencing assembly and analysis. That release added viral genome analysis workflow support for Pacific Biosciences and Oxford Nanopore long-read sequences, including data from PCR-amplified fragments generated according to Artic network protocols. The update was also optimized forgenomic analysis and variant identification to support COVID-19 research.

Lasergene, which serves the molecular biology and genomics markets, is one DNAStar's two product lines. It includes a series of applications for tasks like genome visualization, sequence assembly, sequence alignment, and in silico cloning. DNAStar's molecular visualization and analysis platform, Protean 3D, is technically part of Lasergene as well.

"Protean 3D has a tight integration between its sequence representations and its structural representations through a selection model," Darnell explained.

Lasergene products are "general tools" aimed at anyone in molecular biology or genomics looking to manage pipelines and workflows, according to Grass. He said that a fair number of customers mistakenly refer to the company as Lasergene because the product name is well known in some circles.

The other DNAStar product line, for structural biology applications including structure prediction, docking, and antibody modeling, is called Nova.

NovaFold is the commercialization of I-TASSER, protein structure prediction software developed by University of Michigan bioinformatician Yang Zhang. In 2015, DNAStar licensed the exclusive commercial rights to I-TASSER and markets the technology as part of Protean 3D.

The firm also licenses technology for its NovaDock protein-protein docking software from Cancer Research UK. Darnell said that the company's products represent a mixture of DNAStar-developed tools, freely available external tools like AlphaSeek, and licensed technology.

DNAStar is not directly partnering with DeepMind, which makes some of its AlphaFold technology available through open-source channels.

Grass said that DNAStar has not made any additions or other changes to the AI that AlphaFold provides. "It's something we are always looking at, but right now, we felt it was best to leave it just how it was," he said.

What the company does offer with the new release is the ability to add AlphaFold structure predictions as templates to the core NovaFold software to guide the modeling process toward these predictions. "What we also bring to the table is the additional downstream analysis outside of just coordinate generation," according to Darnell.

Most of the tools in both product lines are integrated on DNAStar's NovaCloud infrastructure, which the firm has been building up for the last five or six years.

DeepMind's AlphaFold had the highest score in the 14th and most recent Critical Assessment of Structure Prediction (CASP) competition in 2020, in which entrants are given the amino acid sequences for about 100 proteins to then predict their structures.

"It certainly excels wonderfully at fold recognition and modeling," Darnell said. He added that AlphaFold will be entered in CASP 15 this summer, a competition that will have a greater focus on predicting multimers.

That is a direction DNAStar wants to go in with NovaFold 2.

"The direct structure prediction of multimers is definitely where I believe the field is certainly looking forward toward, as well as different and better approaches for doing multi-domain proteins," Darnell said. "A tool like AlphaFold can identify and actually model different domains in isolation within a multi-domain sequence."

Darnell also expects to see more activity around protein-protein docking technology in subsequent years.

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This Week’s Awesome Tech Stories From Around the Web (Through May 28) – Singularity Hub

ROBOTICS

Dyson Reveals Its Big BetRobotsJasper Jolly | The GuardianDyson has signaled it is placing a big bet on producing robots capable of household chores by 2030, as it looks to move beyond the vacuum cleaners, fans and dryers that made its founder one of the wealthiest British businessmen. The company, founded by billionaire Sir James Dyson, on Wednesday published photographs of robot arms being used in household settings, including cleaning furniture, a claw picking up plates, and a hand-like machine picking up a teddy bear.

The Big New Idea for Making Self-Driving Cars That Can Go AnywhereWill Douglas Heaven | MIT Technology ReviewWhen [the car veered to the side], Kendall grabbed the wheel for a few seconds to correct it. The car veered again; Kendall corrected it. It took less than 20 minutes for the car to learn to stay on the road by itself, he says. This was the first time that reinforcement learningan AI technique that trains a neural network to perform a task via trial and errorhad been used to teach a car to drive from scratch on a real road.

Quantum Internet Inches Closer With Advance in Data TeleportationCade Metz | The New York TimesWhen data travels this way, without actually traveling the distance between the nodes, it cannot be lost. Information can be fed into one side of the connection and then appear on the other, Dr. Hanson said. The information also cannot be intercepted. A future quantum internet, powered by quantum teleportation, could provide a new kind of encryption that is theoretically unbreakable.

Accused of Cheating by an Algorithm, and a Professor She Had Never MetKashmir Hill | The New York TimesSuddenly [during the pandemic], millions of people were forced to take bar exams, tests and quizzes alone at home on their laptops. To prevent the temptation to cheat, and catch those who did, remote proctoring companies offered web browser extensions that detect keystrokes and cursor movements, collect audio from a computers microphone, and record the screen and the feed from a computers camera, bringing surveillance methods used by law enforcement, employers and domestic abusers into an academic setting.

Walmart Is Expanding Its Drone Deliveries to Reach 4 Million HouseholdsMitchell Clark | The VergeIt sounds like Walmarts not just trying to expand the programs footprintthe company also wants to increase the number of packages its delivering via drone. In its press release, the company says its completed hundreds of deliveries within a matter of months. With the expansion, it says itll have the ability to do more than a million drone deliveries a year.

Tiny Robot Crab Doctors Could Roam the Human Body One DayMonisha Ravisetti | CNETNorthwestern University researchers announced on Wednesday their quite adorable prototype of a crab-shaped mini-robot. It can run. It can jump. Its tiny enough to fit inside the o in this sentence. And its record-breaking. The team calls it the smallest remote-controlled walking robot ever constructed.

The Hype Around DeepMinds New AI Model Misses Whats Actually Cool About ItMelissa Heikkil | MIT Technology ReviewUnsurprisingly, de Freitass announcement triggered breathlesspress coverage that DeepMind is on the verge of human-level artificial intelligence. This is not the first time hype has outstripped reality. Other exciting new AI models, such as OpenAIs text generator GPT-3 and image generator DALL-E, have generated similarly grand claims. For many in the field, this kind of feverish discourse overshadows other important research areas in AI.

Could Nuclear Clocks Drive a Technological Revolution?Ethan Siegel | Big ThinkToday, atomic clocks play an essential role in telecommunications, financial transactions, computers, GPS satellite navigation technologies as well as a variety of scientific applications. We can synchronize clocks around the globe with ~nanosecond precisions. But still, there are limits to what we can do, and those are set by the physical limits of atoms. Yet theres a tremendous hope for surpassing all current limits by more than an order of magnitude: nuclear clocks. Heres the science of how it all works.

Niantic Positions Itself as a Capable Rival to Apple, Meta in Coming AR WarsMark Sullivan | Fast CompanyiAbout once a decade for the last 70 years, a new computing platform arrives and changes the way we work, play, communicate with each other, and lead our lives, Niantic founder John Nanke said of AR during his keynote Tuesday in San Francisco. Were now at the beginning of another one of those shifts, and it could be the most consequential one yet. This transition will truly blend the real and the digital world.i

Scientists CRISPRd Tomatoes to Make Them Full of Vitamin DEd Cara | GizmodoThe tomatoes of the future could help boost your levels of the sunshine vitamin. Researchers in the UK say theyve developed genetically edited tomatoes that can produce high levels of vitamin D with just an hour of ultraviolet light exposure. These edited tomatoes would ideally help provide a rich and plant-based source of the essential nutrient, which is commonly lacking in much of the population.

World Builders Put Happy Face on Superintelligent AIEliza Strickland | IEEE SpectrumOne of the biggest challenges in aworld-building competitionthat asked teams to imagine apositive future with superintelligent AI: Make it plausible. Were not trying to push utopia, [the Future of Life Institutes Ann Yelizarova] says, noting that the worlds built for the contest are not perfect places with zero conflicts or struggles. Were just trying to show futures that are not dystopian, so people have something to work toward, she says.

Humans Could Go Extinct. Heres How and Whos Trying to Stop ItErin Carson | CNETiThe end of the world is such a great concept for giving shape to history, says [Oxfords] Anders Sandberg. We want to know how it ends. We want there to be a meaning or a tragedy or a comedy. Maybe a laugh track at the end of the universe. It turns out, scientists, scholars, policy experts and more are studying this question, trying to decipher how humanitys end could come about, and whether theres anything that can be done to prevent it.

Image Credit: niloy tesla / Unsplash

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Bitcoin vs Ethereum Forbes Advisor UK – Forbes

Bitcoin and Ethereum are the Coca-Cola and Pepsi of the cryptocurrency space. As the number one and two biggest names in the market, theyre often compared against one another.

From premise to prices, the two concepts are very different. However, there are many similarities to be found. Heres a look at how the two systems compare.

Bitcoin and Ethereum are systems, whereas bitcoin (lower case b) and Ether are the cryptocurrencies used by those systems. When comparing the two ecosystems, we need to be clear whether were comparing the technology, the assets or both.

In this article, we will refer to the systems by name and the currencies by their stock symbols. For bitcoin, thats BTC. For Ether, its ETH.

Bitcoin and Ethereum are fundamentally different because the former was designed to enable decentralised finance while the latter was designed to also enable apps and contracts.

While Ethereum does enable payments using its internal ETH cryptocurrency, its scope is much broader than Bitcoins by design.

Both systems use blockchain technology to validate and record transactions, but the way in which they do it is different, with consequences for speed, sustainability and accessibility.

The difference lies in whats known as a consensus mechanism.

A consensus mechanism is a computer algorithm that makes a blockchain viable. It does this by solving whats known as the double spend problem.

A 10 note, once spent, no longer belongs to you, so you cant spend it again. A BTC is a string of computer code, and could be copied infinitely. In theory, this means you could make yourself as rich as you liked by simply making copies of your BTC and spending it over and over again.

However, when you send someone a BTC, your copy is destroyed and a new version of it is created in the recipients account.

This is all recorded on a distributed ledger for the world to see. Since everyone can see on their copies of the ledger that youve spent your BTC, you cant attempt to spend a copied version of it the consensus of ledger holders would be that you were trying to pull a fast one.

Doctoring one transaction is hard enough, but youd actually also have to change every subsequent transaction since each one references its forerunners.

This would take an incredible amount of computing power and effort, plus youd need to control 51% of the distributed ledgers on the network to get the consensus necessary to etch your fake history of transactions onto the blockchain and take your freshly mined crypto as reward.

Bitcoin and Ethereum use different consensus mechanisms.

Bitcoins is called proof of work while Ethereums is called proof of stake.

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Cryptoassets are highly volatile and unregulated in the UK. No consumer protection. Tax on profits may apply.

This consensus mechanism asks participants to carry out complex computations for the chance to become the user who gets to validate a bunch of transactions and add them to the blockchain earning a set amount of crypto in the process..

The work involves guessing, as closely as possible, a unique, alphanumeric string of 64 characters.

There are trillions of possible combinations to these strings, so those with the most powerful computer hardware can make the most guesses per second within the 10-minute window of opportunity, and have the best chance of being the chosen validator.

In order to get a doctored copy of the ledger validated and added to the block, youd need to control at least 51% (a consensus) of the computing power of a network, which would be astronomical. This is how the consensus method prevents fraud.

This work used to be done by hobbyists at home, but the processing power needed increases over time, so the mining process is now the reserve of companies and specialist organisations i.e. those who can afford the hardware and the power needed to run it.

Proof of work systems such as Bitcoin have drawn a lot of criticism for the amount of energy expended by the computer hardware involved. Bitcoin currently uses 19 terawatt hours (TWh) of electricity per year. Thats just under the amount used by the entire nation of Norway.

This consensus mechanism asks participants to stake their own money for the chance to validate transactions and add a block to a blockchain, rather than carry out complex computations.

The more crypto someone stakes, the greater their chances of being chosen to validate a block of transactions to a blockchain and earning a set amount of crypto. The system also discourages bad actors with financial penalties.

Proof of stake stacks the deck in favour of people with more money, but protects against people adding fraudulent records to the blockchain because theyd need to stake at least 51% of the money in the network to control a consensus.

Without the need for powerful computer hardware, proof of stake is considered a more environmentally friendly consensus mechanism than proof of work.

Bitcoin was developed solely to facilitate decentralised payments, that is, to allow people to send and receive payments without an intermediary such as a bank. Ethereum, on the other hand, was designed to do more than just send and receive ETH.

Using blockchain, which provides an immutable record of transactions, Ethereum was designed to facilitate decentralised software such as smart contracts and distributed apps (dApps).

A smart contract is a digital agreement between two or more parties that will execute itself once certain conditions are met.

For example, Account A will release Asset X once it has received Asset Y from Account B. This could be used to make property sales and the transfer or ownership faster and less liable to fraud.

A dApp is an application that isnt controlled by a central authority. Twitter is an example of a centralised app, with users relying on it as an intermediary to send and receive messages. As such, users play by the rules it enforces and the algorithm it uses to control content.

A dApp is distributed on a blockchain, with users able to send and receive data directly without the need for an intermediary. Peepeth is a Twitter-like dApp. It claims that as an app it doesnt optimise for advertising revenues, an issue it says users of centralised apps suffer from.

So while you could say that Bitcoin is larger, but Ethereum is faster, the two arent strictly in competition with each other because theyre designed to do different things. BTC and ETH, on the other hand, are directly comparable.

BTC has certainly been more valuable than ETH, peaking at around $64,000 in November 2021. ETH on the other hand peaked at around $4,600 in the same month.

Despite the stark difference in their values, the two cryptocurrencies values have historically shown strong positive correlation to each other, trending between 0.7 and 0.8 for much of that time (with 1.0 representing the strongest possible correlation) according to coinmetrics.io data.

Regardless, and as is the case with all cryptocurrencies, BTC and ETH are both volatile. Prices are unpredictable and prone to crashes.

The cryptocurrency market is unregulated in the UK. The UK financial watchdog the Financial Conduct Authority (FCA) has issued repeated and stark risk warnings to people thinking of investing in cryptocurrency, saying they should be prepared to lose their entire investments with no recourse to compensation.

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Bitcoin vs Ethereum Forbes Advisor UK - Forbes

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Billionaire Bill Miller Says Upcoming Ethereum Upgrade Will Leave Bitcoin With One Massive Advantage Over ETH – The Daily Hodl

Legendary investor Bill Miller says the upcoming Ethereum (ETH) switch to a proof-of-stake network will saddle Bitcoin (BTC) with one huge advantage over the top altcoin.

In a new interview on The Investors Podcast Network, the billionaire investor says ETHs switch from a proof-of-work to a proof-of-stake consensus mechanism could increase financial inequality, a problem that wouldnt be found on the top crypto asset by market cap.

The other thing with proof of stake is one of the big problems that people talk about as a problem in the United States is inequality. Well, proof of stake basically is the most unequal thing you can imagine, because the rich people make all the decisions.

And if you have more stakes, if you have more Ethereum at stake, meaning you own more of it than somebody else, you get whatever the votes are. Its like if you own more shares than If you own 50% of the shares of Berkshire Hathaway, you can determine whats going to happen with Berkshire Hathaway.

And if you own 50% of the Ethereum, you decide whats going to happen with it, and nobody else can say it. Thats a problem that Bitcoin doesnt have. Its truly democratic.

Miller goes on to say he considers BTC as a sort of insurance against an economic meltdown, citing the political situations of Venezuela, Nigeria, Lebanon, Ukraine, and Afghanistan as examples.

If you had Bitcoin, you were fine. Your Bitcoin is there. You can send it to anybody in the world if you have a phone. And so I consider Bitcoin basically an insurance policy against financial catastrophe of one sort or another.

Miller revealed in January that half of his net worth was invested in Bitcoin.

Bitcoin is changing hands at $28,607 at time of writing, down 1.34% in the last 24 hours, while Ethereum is trading for $1,732, a 1.16% drop over the same timeframe.

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Featured Image: Shutterstock/DMegias

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Billionaire Bill Miller Says Upcoming Ethereum Upgrade Will Leave Bitcoin With One Massive Advantage Over ETH - The Daily Hodl

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Bitcoin could fall to $8,000, a more than 70% plunge, Guggenheim’s Minerd says – CNBC

Bitcoin could drop further and fall to $8,000 from its current levels, Guggenheim Chief Investment Officer Scott Minerd predicted Monday.

That would represent a more than 70% drop to Monday morning's price of just over $30,000.

"When you break below 30,000 [dollars] consistently, 8,000 [dollars] is the ultimate bottom, so I think we have a lot more room to the downside, especially with the Fed being restrictive," Minerd told CNBC's Andrew Ross Sorkin in a "Squawk Box" interview at the World Economic Forum in Davos, Switzerland on Monday.

Minerd is referring to the U.S. Federal Reserve's hiking of interest rates and tightening of monetary policy.

Since falling below $30,000 earlier this month, bitcoin has struggled to rally substantially above that level. It has regularly dipped below $30,000.

Scott Minerd,Guggenheim Partners LLC Global Chief Investment Officer, at the WEF in Davos, Switzerland on May 23rd, 2022.

Adam Galici | CNBC

If Minerd's forecast comes true, it would inflict further pain on bitcoin and the broader cryptocurrency market which has seen around $500 billion wiped off its value in the past month. Bitcoin is down around 24% in the last 30 days alone.

The CIO also said that most crypto is "junk" but that bitcoin and ethereum will survive.

"Most of these currencies, they're not currencies, they're junk," he said.

Even so, he said, "I don't think we've seen the dominant player in crypto yet."

Minerd compared the current situation to the dotcom bubble of the early 2000s.

"If we were sitting here in the internet bubble, we would be talking about how Yahoo and America Online were the great winners," he said. "Everything else, we couldn't tell you if Amazon or Pets.com was going to be the winner."

"I don't think we have had the right prototype yet for crypto," he said, saying that currency needs to store value, be a medium of exchange and unit of account.

"None of these things pass, they don't even pass on one basis," he said. Minerd added that additional technological advances could change that and help create an ecosystem where people get used to using cryptocurrencies for transactions and are confident they will hold their value.

Minerd's comments come after European Central BankPresidentChristine Lagarde said cryptocurrencies are "worth nothing."

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Bitcoin could fall to $8,000, a more than 70% plunge, Guggenheim's Minerd says - CNBC

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