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Quantum computing will bring unimagined innovations to the world when it finally arrives in full glory. Still, quantum remains in the research labs at companies like IBM, Google, and Microsoft. While companies and research institutions are investing billions of dollars to increase the capacity of quantum systems, a time will come in the following years, or decades, when researchers will reach "quantum supremacy." But these large quantum marvels could also jeopardize the security of critical information systems. Researchers, including IBM are working to develop new security algorithms that will be resilient to these attacks.
The Quantum Threat to Security
While quantum can solve computing challenges far beyond what is possible today, its ability to find the factors of large prime numbers makes it the ideal cybersecurity safe cracker once quantum computing systems mature in their scale, quality, and speed. Every computer system and every bit of "secure" data could become vulnerable to attack from quantum-equipped nefarious actors. The World Economic Forum "estimate(s) that over 20 billion digital devices will need to be either upgraded or replaced in the next 10-20 years to use the new forms of quantum-resistant encrypted communication. We recommend that organizations start planning for this now.”
What constitutes "adequate size" might deliver us some false comfort: a 2019 study suggested that a computer with 20 million qubits would take eight hours to break modern encryption. Today's quantum computers are on the order of only 100 qubits. But while that implies that the threat is in the distant future, one must consider that a bad actor doesn't need to wait for the massive quantum system to materialize. The "Steal now, crack later" approach leads to a latent future security threat. Consequently, organizations should deploy quantum-safe security as soon as possible to minimize future risk.
Stopping Quantum Attacks Before They Begin
Consequently, the National Institute of Standards and Technology (NIST), a bureau of the U.S. Department of Commerce, has been conducting an ongoing search for quantum-safe security algorithms that are both secure and efficient. After all, we need our laptops, cars, and mobile phones to also be able to resist attacks from quantum-equipped bad actors. After four rounds of submissions, NIST selected four algorithms from a slate of 82 candidates. IBM Research had submitted 3 of the four chosen algorithms. All submissions have been subjected to research by industry scrutiny by government agencies, academic scientists, and mathematicians. This process is now reaching its conclusion; the NIST is expected to publish standards based on these 4 algorithms sometime in 2024.
The NIST contest covers the two aspects of security that could be vulnerable to quantum computing: public key encapsulation (used for public-key encryption and key establishment) and digital signatures (used for identity authentication and non-repudiation). For the former, NIST selected the CRYSTALS-Kyber algorithm. NIST selected three algorithms for signatures: CRYSTALS-Dilithium, FALCON, and SPHINCS+, with CRYSTALS-Dilithium as the primary algorithm in the signature category.
The Telco Industry Steps Up to Address Quantum Safe
On September 29, GSMA announced the formation of the GSMA Post-Quantum Telco Network Taskforce, of which IBM and Vodafone are initial members, to help define policy, regulation and operator business processes to enhance protections of telecommunications in a future of advanced quantum computing. Since virtually all organizations and sectors conduct commerce on the internet, and the 800 providers whose pipes that carry all the internet traffic, the Telco industry is a good place to start. We expect other sectors to follow suit, perhaps starting with banking, government, and health care.
IBM Adds Quantum-Safe Security to the IBM z16
Given the magnitude of the potential risks, and the predominance of IBM Z systems in security-critical applications, IBM has included future-proof digital signature support in its latest z16 mainframe using CRYSTALS-Kyber and CRYSTALS -Dilithium algorithms selected by NIST. z16 implements this algorithm across multiple layers of firmware to help protect business-critical infrastructure and data from future quantum attacks. IBM has said it is also working to bring these new methods to the broader market.
The IBM z16 is the first quantum-safe server.
IBMIn addition, IBM has developed a multi-step process to assist clients toward rapidly making institutions quantum safe. The company works with clients to identify where they are vulnerable to quantum-based cryptography attacks, assess cryptographic maturity and dependencies, and identify near-term achievable cryptographic goals and projects. The risks clients may face vary substantially based on the type of applications and data an organization handles and the state of its current cryptography.
Conclusions
Quantum computing's potential threat to global information security may seem to be a distant and abstract risk. However, the inevitable advances of quantum technology and the "Steal now, crack later" approach bad actors are undertaking to make quantum-safe a genuine and pressing matter for vendors and IT organizations. IBM wasted no time bringing that technology to market in the IBM z16. IBM Research has contributed three of the four algorithms the NIST quantum-safe contest has selected to be the most viable, secure, and efficient of the 70 techniques evaluated.
Beyond the NIST-approved algorithms, IBM Is working to provide “crypto agility”, helping organizations not only replace the soon-to-fail existing algorithms but also transform their security practices to remain resilient as new threats emerge in the post-quantum world. Creating crypto observability, enabling ongoing monitoring and actions on crypto-related security items, will help keep the world safer from bad actors with virtually unlimited computing capacity at their disposal.
More information can be found at here.
Disclosures: This article expresses the opinions of the authors, and is not to be taken as advice to purchase from nor invest in the companies mentioned. Cambrian AI Research is fortunate to have many, if not most, semiconductor firms as our clients, including Blaize, Cerebras, D-Matrix, Esperanto, FuriosaAI, Graphcore, GML, IBM, Intel, Mythic, NVIDIA, Qualcomm Technologies, Si-Five, SiMa.ai, Synopsys, and Tenstorrent. We have no investment positions in any of the companies mentioned in this article and do not plan to initiate any in the near future. For more information, please visit our website at https://cambrian-AI.com.
In recent years, neuroscientists have tried many types of neural networks to model the firing of neurons in the human brain. In a recent project, the two researchers Whittington and Behrens found that the hippocampus, a structure of the brain critical to memory, works as a particular kind of artificial neural network called transformer.
The fact that we know these models of the brain are equivalent to the transformer means that our models perform much better and are easier to train.
This was said by Whittington who also said that transformers can greatly Boost the neural network's ability to mimic the behavior of the brain and its computations. David Ha from Google Brain said that they are not trying to recreate the brain, but are trying to create a mechanism that can do what the brain does.
Transformers work with the self-attention mechanism in which every input is always connected to every output. An input can be a word, a pixel, or a number in a sequence. The difference with the other neural networks is that in other networks only certain inputs are connected with other inputs. Transformers first appeared five years ago with the BERT and GPT-3, a new revolutionary way for AI to process languages.
Whittington and Behrens tweak the approach of Hopfield network, modifying the transformers in a way to encode the memories as coordinates in higher-dimensional spaces rather than linear sequences as Hopfield and Dmitry Krotov did at MIT-IB Watson AI lab. The two researchers showed also that the model is mathematically equivalent to the model of the grid cell firing patterns that neuroscientists see in fMRI scans. Beharens said transformers as another step to understanding better the brain and having an accurate model, rather than the end of the quest.
I have got to be a skeptic neuroscientist here, I don’t think transformers will end up being how we think about language in the brain, for example, even though they have the best current model of sentences.
Schrimpf, a computational neuroscientist at MIT, who analyzed 43 different neural net models to understand how well they predicted behavior of human neural activity as reported by fMRI and electrocorticography, noted that even the best-performing transformers worked well with words or small sentences and not for larger-scale languages tasks. This is why he claims:
My sense is that this architecture, this transformer, puts you in the right space to understand the structure of the brain, and can be improved with training. This is a good direction, but the field is super complex.
A four-year bachelor’s degree has long been the first rung to climbing America’s corporate ladder.
But the move to prioritize skills over a college education is sweeping through some of America’s largest companies, including Google, EY, Microsoft, and Apple. Strong proponents say the shift helps circumvent a needless barrier to workplace diversity.
“I really do believe an inclusive diverse workforce is better for your company, it’s good for the business,” Ginni Rometty, former IBM CEO, told Fortune Media CEO Alan Murray during a panel last month for Connect, Fortune’s executive education community. “That’s not just altruistic.”
Under Rometty’s leadership in 2016, tech giant IBM coined the term “new collar jobs” in reference to roles that require a specific set of skills rather than a four-year degree. It’s a personal commitment for Rometty, one that hits close to home for the 40-year IBM veteran.
When Rometty was 16, her father left the family, leaving her mother, who’d never worked outside the home, suddenly in the position to provide.
“She had four children and nothing past high school, and she had to get a job to…get us out of this downward spiral,” Rometty recalled to Murray. “What I saw in that was that my mother had aptitude; she wasn’t dumb, she just didn’t have access, and that forever stayed in my mind.”
When Rometty became CEO in 2012 following the Great Recession, the U.S. unemployment rate hovered around 8%. Despite the influx of applicants, she struggled to find employees who were trained in the particular cybersecurity area she was looking for.
“I realized I couldn’t hire them, so I had to start building them,” she said.
In 2011, IBM launched a corporate social responsibility effort called the Pathways in Technology Early College High School (P-TECH) in Brooklyn. It’s since expanded to 11 states in the U.S. and 28 countries.
Through P-TECH, Rometty visited “a very poor high school in a bad neighborhood” that received the company’s support, as well as a community college where IBM was offering help with a technology-based curriculum and internships.
“Voilà! These kids could do the work. I didn’t have [applicants with] college degrees, so I learned that propensity to learn is way more important than just having a degree,” Rometty said.
Realizing the students were fully capable of the tasks that IBM needed moved Rometty to return to the drawing board when it came to IBM’s own application process and whom it was reaching. She said that at the time, 95% of job openings at IBM required a four-year degree. As of January 2021, less than half do, and the company is continuously reevaluating its roles.
For the jobs that now no longer require degrees and instead rely on skills and willingness to learn, IBM had always hired Ph.D. holders from the very best Ivy League schools, Rometty told Murray. But data shows that the degree-less hires for the same jobs performed just as well. “They were more loyal, higher retention, and many went on to get college degrees,” she said.
Rometty has since become cochair of OneTen, a civic organization committed to hiring, promoting, and advancing 1 million Black individuals without four-year degrees within the next 10 years.
If college degrees no longer become compulsory for white-collar jobs, many other qualifications—skills that couldn’t be easily taught in a boot camp, apprenticeship program, or in the first month on the job—could die off, too, University of Virginia Darden School of Business professor Sean Martin told Fortune last year.
“The companies themselves miss out on people that research suggests…might be less entitled, more culturally savvy, more desirous of being there,” Martin said. Rather than pedigree, he added, hiring managers should look for motivation.
That’s certainly the case at IBM. Once the company widened its scope, Rometty said, the propensity to learn quickly became more of an important hiring factor than just a degree.
This story was originally featured on Fortune.com
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Cloud News
Mark Haranas
IBM continues to spend millions to buy hybrid cloud companies, as the company makes its sixth acquisition in 2022 with Dialexa.
IBM continues to spend millions on buying hybrid cloud companies with the unveiling of its acquisition of engineering consulting specialist Dialexa to boost its cloud charge.
Since IBM CEO Arvind Krishna took the reins in April 2020, IBM has acquired more than 25 companies, including many hybrid cloud businesses.
In February alone, IBM acquired cloud consultant services standout Sentaca, as well as Microsoft Azure consultancy all-star Neudesic—with the two purchases squarely aimed at boosting IBM’s hybrid and multi-cloud services capabilities.
[Related: UK To Probe Amazon, Google, Microsoft’s Cloud Dominance]
Looking at the Armonk, N.Y.-based company’s purchase of Dialexa, IBM will gain 300 skilled product managers, designers, full-stack engineers and data scientists. Dialexa will become part of IBM’s Consulting business unit, which spearheads the company’s digital product engineering services in the Americas.
“Dialexa’s product engineering expertise, combined with IBM’s hybrid cloud and business transformation offerings, will help our clients turn concepts into differentiated product portfolios that accelerate growth,” said John Granger, senior vice president of IBM Consulting, in a statement.
Krishna: Hybrid Cloud A ‘Competitive Advantage’
Dialexa marks IBM’s sixth purchase in 2022 with the goal of boosting its hybrid cloud and artificial intelligence abilities.
Along with buying Dialexa, Sentaca and Neudesic, IBM has also acquired Randori, an attack surface management cybersecurity specialist that helps protect hybrid cloud environments.
Earlier this year, IBM’s CEO said hybrid cloud and artificial intelligence are top of mind for his company in terms of investment and the future.
“We are integrating technology and expertise—from IBM, our partners and even our competitors—to meet the urgent needs of our clients, who see hybrid cloud and AI as crucial sources of competitive advantage,” Krishna said in March. “And we are ready to be the catalyst of progress for our clients as they pursue the digital transformation of the world’s mission-critical businesses.”
In 2021, IBM’s hybrid cloud revenue jumped 19 percent compared with 2020, comprising 35 percent of its total revenue.
IBM’s Acquisition Of Dialexa
Based in Dallas and Chicago, Dialexa delivers a suite of digital product engineering services to help customers create transformative products to drive business outcomes.
Dialexa’s 300-strong engineers and skilled IT experts advise and create custom digital products for customers, which include Deere & Company, Pizza Hut U.S. and Toyota Motor North America. Financial terms of the Dialexa deal were not disclosed.
IBM said Dialexa provides deep experience delivering end-to-end digital product engineering services consisting of strategy, design, build, launch and optimization services across cloud platforms including Amazon Web Services and Microsoft Azure.
“Digital product engineering represents the tip of the spear for competitive advantage,” said Dialexa CEO Scott Harper in a statement. “IBM and Dialexa’s shared vision for delivering industry-defining digital products could be a game-changer.”
IBM (IBM) closed at $127.73 in the latest trading session, marking a +0.36% move from the prior day. This move lagged the S&P 500's daily gain of 0.69%. At the same time, the Dow added 0.64%, and the tech-heavy Nasdaq lost 0.2%.
Coming into today, shares of the technology and consulting company had lost 8.02% in the past month. In that same time, the Computer and Technology sector lost 14.62%, while the S&P 500 lost 9.94%.
Investors will be hoping for strength from IBM as it approaches its next earnings release. On that day, IBM is projected to report earnings of $1.88 per share, which would represent a year-over-year decline of 25.4%. Meanwhile, our latest consensus estimate is calling for revenue of $13.75 billion, down 21.96% from the prior-year quarter.
Looking at the full year, our Zacks Consensus Estimates suggest analysts are expecting earnings of $9.39 per share and revenue of $59.9 billion. These totals would mark changes of +18.41% and -15.38%, respectively, from last year.
Investors might also notice recent changes to analyst estimates for IBM. These revisions typically reflect the latest short-term business trends, which can change frequently. As such, positive estimate revisions reflect analyst optimism about the company's business and profitability.
Our research shows that these estimate changes are directly correlated with near-term stock prices. To benefit from this, we have developed the Zacks Rank, a proprietary model which takes these estimate changes into account and provides an actionable rating system.
The Zacks Rank system, which ranges from #1 (Strong Buy) to #5 (Strong Sell), has an impressive outside-audited track record of outperformance, with #1 stocks generating an average annual return of +25% since 1988. Over the past month, the Zacks Consensus EPS estimate has moved 0.88% lower. IBM is currently a Zacks Rank #3 (Hold).
Digging into valuation, IBM currently has a Forward P/E ratio of 13.56. This represents a no noticeable deviation compared to its industry's average Forward P/E of 13.56.
Meanwhile, IBM's PEG ratio is currently 1.94. This metric is used similarly to the famous P/E ratio, but the PEG ratio also takes into account the stock's expected earnings growth rate. Computer - Integrated Systems stocks are, on average, holding a PEG ratio of 1.77 based on yesterday's closing prices.
The Computer - Integrated Systems industry is part of the Computer and Technology sector. This group has a Zacks Industry Rank of 162, putting it in the bottom 36% of all 250+ industries.
The Zacks Industry Rank gauges the strength of our individual industry groups by measuring the average Zacks Rank of the individual stocks within the groups. Our research shows that the top 50% rated industries outperform the bottom half by a factor of 2 to 1.
To follow IBM in the coming trading sessions, be sure to utilize Zacks.com.
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RESEARCH TRIANGLE PARK – In a move to enhance its hybrid cloud and AI capabilities, IBM will buy the digital product engineering consulting services firm Dialexa in a deal that will close later this year.
IBM announced the deal in a statement, which also notes that the purchase of the firm will “deepen IBM’s product engineering expertise and provide end-to-end digital transformation services for clients.”
When the deal closes, Dialexa will become the sixth company bought by IBM in 2022.
But Big Blue has been on a buying frenzy since April 2020, when Arvind Krishna became the company’s CEO. According to the company, IBM has acquired more than 25 other firms, with 13 to bolster IBM Consulting.
The latest acquisition of Dialexa points toward how IBM may grow its consulting services presence.
“In this digital era, clients are looking for the right mix of high-quality products to build new revenue streams and Boost topline growth,” said John Granger, senior vice president, IBM Consulting, in a statement. “Dialexa’s product engineering expertise, combined with IBM’s hybrid cloud and business transformation offerings, will help our clients turn concepts into differentiated product portfolios that accelerate growth.”
The company’s 300 employees are based in Dallas and in Chicago, and will join IBM Consulting, according to the statement. Among the firm’s clients is Toyota Motor North America, which will invest $2.5 billion in North Carolina to build the company’s first U.S. electric battery manufacturing plant in Randolph County.
© IBM null
IBM has announced the latest version of its Linux-focused mainframe - the LinuxOne Emperor 4 as the company leads with promises of reduced energy consumption and increased sustainability.
While the z16 mainframe, which was announced by the company in April 2022, is optimized for IBM’s z/OS operating system, the LinuxOne Emperor 4 is designed to support Linux operating systems in a bid to obtain a significant portion of the Linux market.
Big Blue’s latest mainframe supports 32 Telum processors and can provide up to 40TB of RAIM. The Emperor 4 also provides “seven nines” of availability, which should translate to three seconds of downtime per year.
Mainframes for Linux distros are increasingly popular among financial services organizations, with Citibank being a user of IBM’s LinuxOne mainframes, combined with the MongoDB database.
With its latest iteration, it’s clear that IBM’s focus is on increasing environmental pressures. In a release, it claims that the Emperor 4 “can reduce energy consumption by 75%, space by 50%, and the CO2e footprint by over 850 metric tons annually.”
This expression of commitment towards creating more sustainable products goes hand-in-hand with IBM’s own research which suggests that around half of the CEOs that took part saw sustainability as their highest priority, and indeed one of their greatest challenges.
The integration of artificial intelligence inference should also serve to Boost latency.
Availability for the IBM LinuxOne Emperor 4 is scheduled for September 14, 2022, with entry- and mid-range models set to follow in the first half of 2023.
Via VentureBeat
New Jersey, United States, Oct. 14, 2022 /DigitalJournal/ The Artificial Intelligence (AI) in Energy Market research report provides all the information related to the industry. It gives the markets outlook by giving authentic data to its client which helps to make essential decisions. It gives an overview of the market which includes its definition, applications and developments, and manufacturing technology. This Artificial Intelligence (AI) in Energy market research report tracks all the recent developments and innovations in the market. It gives the data regarding the obstacles while establishing the business and guides to overcome the upcoming challenges and obstacles.
AI optimizes energy networks by managing energy flows between homes, businesses, storage batteries, renewable energy sources, microgrids, and the power grid itself. This reduces energy waste while increasing consumer engagement with energy consumption. The market is driven by rapid power demand and a lack of information networks in power generation. Artificial intelligence (AI) is an extension of computer technology that highlights the formation of intelligent machines that function and react like humans. The energy and utility sector produces and distributes energy consisting of oil and gas, power generation and others.
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Some of the Top companies Influencing this Market include:Ibm Corporation, Microsoft Corporation, Accenture Plc, Amazon Web Services, Inc., Intel Corporation, Oracle Corporation, Sap Se, Huawei Technology, Cisco Systems, General Electric Company, Rockwell Automation, C3.Ai, Autogrid Systems, Hcl Technologies, And Wipro Limited.
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Power Industry (Generation,Transmission,Distribution), Oil & Gas Industry (Upstream, Midstream, Downstream),
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Table of Contents
Global Artificial Intelligence (AI) in Energy Market Research Report 2022 – 2029
Chapter 1 Artificial Intelligence (AI) in Energy Market Overview
Chapter 2 Global Economic Impact on Industry
Chapter 3 Global Market Competition by Manufacturers
Chapter 4 Global Production, Revenue (Value) by Region
Chapter 5 Global Supply (Production), Consumption, Export, Import by Regions
Chapter 6 Global Production, Revenue (Value), Price Trend by Type
Chapter 7 Global Market Analysis by Application
Chapter 8 Manufacturing Cost Analysis
Chapter 9 Industrial Chain, Sourcing Strategy and Downstream Buyers
Chapter 10 Marketing Strategy Analysis, Distributors/Traders
Chapter 11 Market Effect Factors Analysis
Chapter 12 Global Artificial Intelligence (AI) in Energy Market Forecast
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