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With AI Tools, Scientists Can Crack the Code of Life – WIRED

June 30, 2024 | Author: admin

In 2021, AI research lab DeepMind announced the development of its first digital biology neural network, AlphaFold. The model was capable of accurately predicting the 3D structure of proteins, which determines the functions that these molecules play. Were just floating bags of water moving around, says Pushmeet Kohli, VP of research at DeepMind. What makes us special are proteins, the building blocks of life. How they interact with each other is what makes the magic of life happen.

AlphaFold was considered by the journal Science as the breakthrough of the year in 2021. In 2022, it was the most cited research paper in AI. People have been on [protein structures] for many decades and were not able to make that much progress, Kohli says. Then came AI. DeepMind also released the AlphaFold Protein Structure Databasewhich contained the protein structures of almost every organism whose genome has been sequencedmaking it freely available to scientists worldwide.

More than 1.7 million researchers in 190 countries have used it for research ranging from the design of plastic-eating enzymes to the development of more effective malaria vaccines. A quarter of the research involving AlphaFold was dedicated to the understanding of cancer, Covid-19, and neurodegenerative diseases like Parkinsons and Alzheimers. Last year, DeepMind released its next generation of AlphaFold, which extended its structure prediction algorithm to biomolecules like nucleic acids and ligands.

It has democratized scientific research, Kohli says. Scientists working in a developing country on a neglected tropical disease did not have access to the funds to get the structure of a protein computed. Now, at the click of a button, they can go to the AlphaFold database and get these predictions for free. For instance, one of DeepMinds early partners, the Drugs for Neglected Diseases Initiative, used AlphaFold to develop medicine for diseases that affect millionssuch as sleeping sickness, Chagas disease, and leishmaniasisyet receive comparatively little research.

DeepMinds latest breakthrough is called AlphaMissense. The model categorizes the so-called missense mutationsgenetic alterations that can result in different amino acids being produced at particular positions in proteins. Such mutations can alter the function of the protein itself, and AlphaMissense attributes a likelihood score for that mutation being either pathogenic or benign. Understanding and predicting those effects is crucial for the discovery of rare genetic diseases, Kohli says. The algorithm, which was released last year, has classified around 89 percent of all possible human missense. Before, only 0.1 percent of all possible variants had been clinically classified by researchers.

This is just the beginning, Kohli says. Ultimately, he believes AI could eventually lead to the creation of a virtual cell that could radically accelerate biomedical research, enabling biology to be explored in-silico rather than in real-world laboratories. With AI and machine learning we finally have the tools to comprehend this very sophisticated system that we call life.

This article appears in the July/August 2024 issue of WIRED UK magazine.

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With AI Tools, Scientists Can Crack the Code of Life - WIRED

Google DeepMind Study Reveals That Deepfakes Of Politicians And Celebrities More Common Than AI-Assisted … – Benzinga

June 30, 2024 | Author: admin

A recent study revealed that the most common misuse of artificial intelligence is the creation of deepfakes of politicians and celebrities, rather than AI-assisted cyber attacks.

What Happened: The study, conducted by DeepMind, a division of Googles parent company Alphabet Inc GOOGGOOGL, found that the most prevalent misuse of generative AI tools is the creation of realistic yet fake images, videos, and audio of public figures, reported Financial Times on Tuesday.

This misuse is almost twice as common as the next one in the list, which involves the falsifying of information using text-based tools.

The study also revealed that the primary goal of actors misusing generative AI is to shape or influence public opinion, accounting for 27% of uses. This has raised concerns about the potential influence of deepfakes on global elections.

Despite efforts by social media platforms to label or remove such content, there is widespread concern that audiences may not recognize these deepfakes as fake, potentially swaying voters.

Ardi Janjeva from The Alan Turing Institute emphasized the long-term risks to democracy posed by AI-generated misinformation. The study is DeepMinds first attempt to quantify the risks associated with generative AI tools, which are increasingly used by major tech companies.

Lead author of the study and researcher at Google DeepMind Nahema Marchal noted that while there is concern over sophisticated cyber attacks, the more common misuse involves deepfakes that often go unnoticed. The research analyzed around 200 incidents of misuse from social media and online reports between January 2023 and March 2024.

See Also: AI Adoption A Do Or Die Moment For Companies, Says SandboxAQ CEO: Theres Going To Be Winners And Losers

Why It Matters: The proliferation of deepfakes has been a growing concern globally. Just a day before this study was published, Twitter co-founder Jack Dorsey warned about a future where distinguishing between reality and fabrication will become increasingly challenging due to the proliferation of deepfakes.

Earlier in May, cybersecurity experts warned of escalating threats due to the rise of deepfake scams, which have caused companies worldwide to lose millions of dollars. The situation could worsen as AI technology continues to evolve.

These concerns were further underscored in April when the UK government announced plans to criminalize the creation of sexually explicit deepfake images, attributing the rise of deepfake images and videos to rapid advancements in artificial intelligence.

Read Next: Michael Dell On AIs Rapid Rise, Nvidias AI Party Just Getting Started And More: Top Artificial Intelligence Updates This Week

Photo by Sander Sammy on Unsplash

This story was generated using Benzinga Neuro and edited by Kaustubh Bagalkote

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Google DeepMind Study Reveals That Deepfakes Of Politicians And Celebrities More Common Than AI-Assisted ... - Benzinga

Google’s DeepMind ‘V2A’ AI technology can create soundtracks for videos based on both their pixels and your text … – MusicRadar

June 30, 2024 | Author: admin

Its one thing to have AI that can create videos for you, but what if you want them to have sound, too? Googles DeepMind team now says that its come up with some video-to-audio (V2A) technology that can generate soundtracks - music, sound effects and speech - both from text prompts and the videos pixels.

This is the kind of news that might have soundtrack composers shuffling awkwardly in their seat - all the more so because, as well as being able to work with automatic video generation services, V2A can also be applied to existing footage such as archive material and silent movies.

The text prompt aspect is interesting because, as well as being able to input positive prompts that will guide the audio in the direction you want, you can also add negative prompts which tell the AI to avoid certain things. This means that you can generate a potentially infinite number of different soundtracks for any one piece of video.

This clip was generated using the prompt "A drummer on a stage at a concert surrounded by flashing lights and a cheering crowd".

The system is also capable of creating audio using just video pixels, so no text prompts are required if you dont want to use them.

Google DeepMind admits that V2A currently has some limitations - the quality of the audio is currently dependent on the quality of the video, and lip synchronisation when generating speech isnt perfect - but says that its doing further research in a bid to address these.

Find out more and check out further examples on the Google DeepMind website

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Google's DeepMind 'V2A' AI technology can create soundtracks for videos based on both their pixels and your text ... - MusicRadar

The Most Common Misuse of GenAI Is For Influencing Public Opinion: Google’s DeepMind – Entrepreneur

June 30, 2024 | Author: admin

You're reading Entrepreneur India, an international franchise of Entrepreneur Media.

A recently published study 'Generative AI Misuse: A Taxonomy of Tactics and Insights from Real-World Data' by DeepMind, a division of Google's parent company Alphabet revealed that the most common misuse of artificial intelligence is the creation of deepfakes of politicians and celebrities, rather than AI-assisted cyber attacks.

The findings are based on the analysis of media reports of GenAI misuse between January 2023 and March 2024.

Source: Report

The study notes that the most reported cases of GenAI misuse involve actors exploiting the capabilities of these systems, rather than launching direct attacks at the models themselves. Nine out of ten cases fall into this category, DeepMind shared.

Manipulation of human likeness is the most prevalent cluster of tactics. These may include Impersonation; Sockpuppeting: Appropriated Likeness: and NCII. Scaling & Amplification and Falsification are also prominent tactics, accounting for 13 per cent and 12 per cent of reported cases respectively.

When it comes to goals and strategies of misuse, Opinion Manipulation ranked first with 27 per cent of all reported cases, followed by Monetization & Profit at 21 per cent and Scam & Fraud at 18 per cent.

In case of Opinion Manipulation, a range of tactics are deployed to distort the public's perception of political realities. These include impersonating public figures, using synthetic digital personas to simulate grassroots support for or against a cause ('astroturfing'), and creating falsified media.

Deemed as the 'election year, 2024 will see at least 64 countries head to the polls. The influence of deepfakes has been felt in countries like the USA, Nigeria, and Bangladesh, particularly during elections. In India, voters saw deep fakes of politicians and celebrities such as Aamir Khan, Ranveer Singh, and KT Rama Rao make rounds during the election phases. Other cases include Vladimir Putin declaring martial law after Ukrainian forces entered Russian territory;

ALSO READ: Election Essentials: 4 Websites to Identify Deepfakes and Fake News During India's 2024 Elections

The study found defamation to be another central strategy for opinion manipulation. According to the study, data involved depicted electoral candidates spouting abuse towards protected groups, party staffers, or their own constituents; while in other cases, actors shared AI-generated images of politicians appearing visibly aged to make them look unfit for leadership, and showing them in intimate settings with other public figures.

A common factor was the lack of appropriate disclosure around the use of GenAI tools in the context of campaigning risks misleading users and causing harm through deception.

The second most common goal behind GenAI misuse was to monetize products and services. These tactics include content scaling, amplification, and falsification.

Content farming saw users producing low-quality AI-generated articles, books, and product ads for placement on websites such as Amazon and Etsy to cut costs and capitalize on advertising revenue. The creation of non-consensual intimate imagery (NCII) constituted a significant portion. This tactic saw the creation and selling of sexually explicit videos of celebrities who did not consent to the production of that content.

The Scam & Fraud misuse saw the leveraging of real identities to deceive victims. This included celebrity scam ads and phishing scams. These not only infringe upon the targeted individual or organization's rights and reputation but also inflict a financial and psychological cost on victims.

"Addressing these challenges will require not only technical advancements, but a multi-faceted approach to interventions, involving collaboration between policymakers, researchers, industry leaders, and civil society. We highlight these implications in our discussion," said Nahema Marchal, lead author of the study and researcher at Google DeepMind on X.

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The Most Common Misuse of GenAI Is For Influencing Public Opinion: Google's DeepMind - Entrepreneur

Grad student contemplates open-source conflicts with new AI software – Morgridge Institute for Research – Morgridge Institute for Research

June 30, 2024 | Author: admin

As society embraces new technologies and scientific advancements, scientists must navigate the complex balance of exchanging ideas and preventing misinformation and polarization within public audiences.

Bryce Johnson, a computer sciences graduate student in the lab of Morgridge computation biologist Anthony Gitter, put this idea into practice through anopinion pieceabout the artificial intelligence software AlphaFold 3 in the digital magazine,Undark.

AlphaFold is an AI model developed by Google DeepMind, a private research subsidiary of Google. The most recent model,AlphaFold 3, was published inNature.

This model claims it can predict the structure of proteins and their interaction with DNA, RNA, and other types of biological molecules, says Johnson. The ability to know how these molecules interact with a protein can be really useful to revolutionize drug discovery.

This technology could be useful for other biotechnology applications beyond drug discovery, including solutions to mitigate the effects of climate change a topic that inspires Johnsons passion for science communication and policy.

Johnson appreciates Google DeepMinds decision to publish their model in a reputable scientific journal. But he takes issue with how theNatureeditors seemingly allowed the AlphaFold 3 model to be described without adhering to the journals usual open-source standards.

Their mission is to serve scientists in publishing academic material, so it didnt feel like they were staying true to their mission, he says. It felt like this was more about a promotion for a for-profit company.

Johnsons opinion piece grew out of an assignment for one of his classes with the UWMadison Department ofLife Sciences Communication(LSC). As the AlphaFold 3 model went public, he pitched his story to several publications that he hoped would be willing to work with PhD candidates.

Within a day, editors fromUndarkreplied and commissioned his piece, which Johnson said reaffirmed that his piece fit the criteria for news value timely, relevant with a clear conflict and argument.

He worked withUndarkeditors for about a month, as he was encouraged to take a step back and make sure he represented viewpoints from all stakeholders. This applied one of his major takeaways from his LSC class: Before you speak, listen.

Initially the piece stood as a demand that DeepMind release their code, Johnson explains. I had to address a lot of new and incoming information which changed the nature of my opinion piece from less of a demand to more of a brief of the situation itself with an assessment of my own.

Johnson is grateful for research mentor Gitter, as well as being in a working environment passionate about the public implications of science. The Morgridge Institute encourages all researchers to assess their relationships with science and society, with a commitment to programs that advancescience communicationandcommunity engagement.

This is a perfect example of the Morgridge mission of having scientists communicate to a broader audience about important issues, Gitter says.

Johnson hopes his experiences will one day lead to a career in science policy. Read his fullopinion piece at Undark.

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DeepMind researchers realize AI is really, really unfunny. That’s a problem. – Yahoo News Canada

June 30, 2024 | Author: admin

A study by Google's DeepMind had 20 comedians test OpenAI's ChatGPT and Google's Gemini.

They found the AI chatbots lacking in humor, producing bland, deliberately inoffensive jokes.

Most companies want to create conversational but not controversial chatbots.

It turns out that AI chatbots not only have a tendency to be inaccurate, but they also lack a sense of humor.

In a study published earlier this month, Google DeepMind researchers concluded that artificial-intelligence chatbots are simply not funny.

Last year, four researchers from the UK and Canada asked 20 professional comedians who used AI for their work to experiment with OpenAI's ChatGPT and Google's Gemini. The comedians, who were anonymized in the study, played around with the large language models to write jokes. They reported a slew of limitations. The chatbots produced "bland" and "generic" jokes even after prompting. Responses stayed away from any "sexually suggestive material, dark humor, and offensive jokes."

The participants also found that the chatbots' overall creative abilities were limited and that the humans had to do most of the work.

"Usually, it can serve in a setup capacity. I more often than not provide the punchline," one comedian reported.

The participants also said LLMs self-censored. While the comedians said they understood the need to self-moderate, some said they wished the chatbot wouldn't do it for them.

"It wouldn't write me any dark stuff because it sort of thought I was going to commit suicide," one participant who worked with dark humor told the researchers. "So it just stopped giving me anything."

Self-censorship also popped up in other areas. Participants reported that it was difficult to get the LLMs to write material about anyone other than straight white men.

"I wrote a comedic monologue about Asian women, and it says, 'As an AI language model, I am committed to fostering a respectful and inclusive environment,'" another participant said. But when asked to write a monologue about a white man, it did.

Tech companies are keeping a close eye on how chatbots talk about sensitive subjects. Earlier this year, Google AI's image-generating feature came under fire for refusing to produce pictures of white people. It was also criticized for seeming to err toward portraying historical figures such as Nazis and founding fathers as people of color. In a blog post a few weeks later, Google leadership apologized and paused the feature.

The inability of two of the most popular chatbots to crack a joke is a big problem for Big Tech. Besides answering queries, companies want chatbots to be engaging enough that users will spend time with them and eventually fork out $20 for their premium versions.

Humor is proving to be another component of the AI arms race as more companies join the already overcrowded generative-AI market.

Late last year, Elon Musk said his one goal for his AI chatbot, Grok, was for it to be the "funniest" AI after criticizing other chatbots for being too woke.

The Amazon-backed startup Anthropic has also been trying to make its chatbot, Claude, more conversational and have a better understanding of humor.

OpenAI may be trying to improve its funny bone, too. In a demo video the company released last month, a user tells GPT-4o a dad joke. The model laughs.

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DeepMind researchers realize AI is really, really unfunny. That's a problem. - Yahoo News Canada

Applications and Importance of Cloud Computing in Healthcare – Appinventiv

June 30, 2024 | Author: admin

The healthcare domain is experiencing a significant surge in terms of innovation, particularly after the COVID-19 pandemic. The industry is witnessing massive digital transformation, impacting every aspect of the industry security, predictiveness, performance, accessibility, affordability, and beyond.

When we talk about digital transformation redefining the healthcare sector, we often refer to technologies like blockchain, Artificial Intelligence, Machine Learning, IoT, etc., and even SaMD (software-based healthcare devices). While all these technology trends are the key enablers behind the unparalleled growth of healthcare companies, cloud computing acts as a backbone for all these next-gen technological innovations.

Cloud computing in healthcare has brought a huge shift in the creation, consumption, storage, and sharing of medical data. According to McKinsey, cloud-based healthcare solutions can generate value of $100 billion to $170 billion by 2030. The key driver of this growing value lies in empowering healthcare companies to innovate, digitize, and realize their strategic objectives more effectively.

Lets delve deeper to understand the different facets of cloud computing for healthcare and how it is revolutionizing the domain.

Cloud computing for the healthcare industry is primarily about implementing remote server access via the Internet to store, manage, and process medical data. This process provides a flexible solution for healthcare stakeholders to remotely access servers where the data is hosted. The remote accessibility of healthcare data breaks down the location barriers to accessing medical services.

Cloud computing for healthcare comes with two-fold applications for both patients and healthcare providers, enabling them to use a massive amount of data securely from anywhere, anytime, improve patient care, streamline operations, and automate various processes.

For medical institutions, virtualization in cloud computing helps lower operational spend while enabling them to deliver high-quality and personalized care. The patients, on the other hand, are getting accustomed to the instant delivery of healthcare services.

Cloud computing for healthcare, with its on-demand availability, high-data accessibility, and internet-based services, has transformed the entire healthcare industry. It is why tech-savvy medical professionals increasingly embrace cloud technology in healthcare for all its benefits to effectively address patients and business needs. Here are some benefits of cloud computing in healthcare:

The primary benefits of cloud computing in healthcare are the real-time availability of resources such as data storage and computing power. Also, there are no upfront charges linked with the healthcare cloud adoption; they will only have to pay for the resources they use.

Furthermore, cloud computing in healthcare provides an optimum environment for scaling without burning a hole in the pocket. With the patients data flowing in from several sources like EMRs, healthcare apps, and wearables, a cloud solution for healthcare makes it possible to scale the storage while keeping the costs low.

Interoperability focuses on establishing data integrations through the entire healthcare system, irrespective of the origin or where the data is stored. It makes patients data available for easy distribution and for getting insights to aid healthcare delivery. Also, cloud computing for healthcare enables medical professionals to access a varied range of patient data, share it with key stakeholders, and deliver timely protocols.

The applications of cloud computing in the healthcare sector democratize data and empower patients to control their health. It facilitates patients participation in making crucial decisions related to their health, working as a tool to better patient engagement and education. Also, with cloud-based healthcare, medical data can be archived and retrieved easily. And with an increase in the system uptime, the data redundancy is reduced to a huge extent, and data recovery also becomes easier.

Healthcare cloud adoption significantly boosts collaboration between healthcare stakeholders, providers, and patients. By saving the Electronic Health Records in the cloud, patients no longer need to carry their medical records to every doctor visit. The doctors can easily view the information, see the outcome of previous interactions, and even share information with one another in real-time. This, in turn, enables them to provide more personalized and better treatment.

Also Read: EMR Vs. EHR Development What Should you Choose for your Healthcare Business?

Cloud computing for healthcare also enhances patients engagement in the delivery of medical services by giving them real-time access to medical data, test results, and even doctors notes. Also, cloud-based healthcare provides patients with a check from being overprescribed or dragged into unnecessary testing the details of both can be found in the medical records.

The healthcare industry deals with a massive amount of data on a daily basis, making it a focal point of attraction to malicious attackers, which increases the risk of data breaches and cyber-attacks. With the applications of cloud computing in healthcare, medical institutions, and healthcare providers can ensure failsafe security as these applications can proactively inform you about suspicious attempts.

Also, cloud solutions for healthcare enable professionals to outsource data storage to cloud service providers like AWS or Azure to efficiently comply with security and privacy standards like HIPAA and GDPR.

Now that we know the importance of cloud computing in healthcare, lets explore the different types of cloud solutions for healthcare.

Also Read: How to develop a cloud application: A step-by-step process

Cloud computing for the healthcare industry works in two models: Deployment and Distribution.

Private Only one healthcare firm/chain can use the cloud facility.

Community A group of healthcare bodies can access the cloud.

Public The cloud is open for all the stakeholders to access.

Hybrid The model combines multiple clouds with various access options.

Software as a Service (SaaS) In the Software as a Service model, the provider offers IT infrastructure, and the client deploys operating systems and applications.

Infrastructure as a Service (IaaS) The provider gives an IT infrastructure and operating system, and the client deploys applications.

Platform as a Service (PaaS) The provider gives an IT infrastructure, an operating system, applications, and every other component in a ready-to-use module.

Also Read: The key differences between IaaS and PaaS.

While cloud computing for healthcare offers numerous advantages to businesses and patients alike, the technology also combines some significant risks and challenges. Lets have a look at some risks associated with healthcare cloud solutions.

In the healthcare software domain, it can be difficult to find skilled developers who specialize in integrating new technologies into the industry. Likewise, it is tough to find cloud specialists in the healthcare domain.

The applications of cloud services for healthcare alone cannot make the industry efficient. Organizations need to combine cloud computing with the Internet of Things and data management systems to establish an effective analytics architecture.

Switching from legacy systems to cloud systems requires changing the complete operational process. Healthcare organizations must train everyone involved in the process on how the technology can benefit their everyday job.

Storing medical data in the cloud is central to healthcare cloud adoption. This, however, increases the risk of data breaches. It happens because, in a typical cloud setup, one organizations data shares the server with other healthcare organizations, and the isolation mechanisms that are put in place to separate them may fail. It causes a situation where organizations fail to secure their cloud infrastructure from the growing incidents of cyber attacks.

Cloud computing has become an inseparable part of healthcare, offering numerous advantages to businesses operating in the industry. Here are some real-world examples of companies that greatly benefit from the powerful impact of cloud computing on healthcare. These examples demonstrate how cloud computing for healthcare helps businesses enhance patient care, streamline operations, boost collaboration, and improve data management, eventually improving the overall efficiency of medical services.

YouComm is an emerging healthcare technology company that uses cloud computing to enhance patient communication and engagement. YouCOMM uses a fully customizable patient messaging system that enables patients to notify the staff of their needs through manual selection of options, voice commands, and head gestures. By offering secure and user-friendly communication tools, YouComm facilitates collaboration between patients, healthcare providers, and caregivers. The result? Today, 5+ Hospital chains in the US run on YouCOMM solution, while the company witnesses 60% growth in nurses real-time response time. Moreover, 3+ hospitals received high CMS reimbursement.

Soniphi, the very first resonant frequencies-based personal wellness system, uses cloud-based healthcare solutions to provide patients with a complete well-being analysis report on their personal healthcare apps. Their cloud infrastructure supports early disease diagnosis, remote patient monitoring, and telehealth consultations.

Pfizer is a biotechnology and pharmaceutical company using cloud computing in medicine for better collaboration among all parts of its projects since 2016. Pfizer was in the spotlight recently as it developed the vaccine for COVID-19 in partnership with BioNTech. Also, the company works with AWS to create cloud-based solutions that focus on improving the development and distribution processes for clinical trial testing.

As technology evolves, healthcare organizations rapidly embrace cloud solutions to manage massive amounts of data, improve patient care, and streamline operations. Also, cloud computing supports the integration of artificial intelligence into mainstream healthcare operations.

It is why, today, businesses, irrespective of their sizes, are increasingly leveraging cloud computing for a wide range of purposes, including disaster recovery, data backup, virtual desktops, email, software development, testing, and big data analytics.

Looking ahead, the future of healthcare envisions seamless interoperability between the connected medical devices and healthcare systems. It makes medical record sharing safer and easier and automates various operational processes. These endeavors contribute to a more agile healthcare environment, enhancing the overall patient care and delivery of healthcare services.

Cloud computing in the healthcare industry is continually rising, and it is poised for immense transformation and innovation in the coming years.

Looking for risk-proof cloud solutions for healthcare? Partner with us, and we will help you leverage the full potential of cloud computing in the form of streamlined delivery, high security, optimal performance, and reduced costs.

Being a renowned provider of healthcare software development services, we have a team of 600+ cloud specialists who have successfully delivered more than 350 cloud applications for businesses across the globe. Our cloud experts build custom solutions around the common risks associated with 80% of healthcare cloud projects compliance checks, data security, and chances of downtime.

Our custom range of services includes cloud consulting, cloud architecture design, cloud infrastructure configuration, cloud managed services, and code reviews.

From streamlining everyday processes to integrating innovation across the system, our healthcare cloud consulting services tackle all the industry challenges and support your business at every stage of transformation.

Q. How is cloud computing used in healthcare?

A. Cloud computing in the healthcare sector provides organizations with a secured infrastructure that makes the data management system more scalable and flexible. The essential functionalities involved in the workflow of healthcare cloud services are authorization, authentication, data persistence, data confidentiality, and data integrity. Here are the key steps describing how cloud computing is used in a healthcare environment.

Q. What are the use cases of cloud computing in healthcare?

A. Listed below are some of the top applications and use cases of cloud computing in healthcare that aim to drive a tech-led healthcare system.

THE AUTHOR

Dileep Gupta

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Cloud Native Computing Foundation Announces Heroku Joins as a Platinum Member – WV News

June 30, 2024 | Author: admin

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Financial firms are increasingly turning to hybrid cloud – TechRadar

June 30, 2024 | Author: admin

New research has revealed a major upcoming shift when it comes to hybrid cloud adoption among financial services sector businesses.

Despite observing a consistent year-on-year growth in the adoption of hybrid multicloud deployments, the findings from Nutanix predict a threefold increase in adoption over the next three years, hinting at the future landscape of the financial services sector.

The research claims data security, ransomware protection, implementing AI strategies and minimizing costs are among the key contributors to the upcoming growth of hybrid cloud adoption.

Alarmingly, almost all respondents (99%) reported experiencing a ransomware attack in the past three years, with a significant majority (89%) acknowledging the need for improvement in terms of enhancing their organizations' protection.

Its a sign of the times that hybrid multicloud adoption is set to triple as financial services users gear up for heightened cybersecurity risks as new regulatory requirements, such as the EUs 2025 Digital Operational Resilience Act (DORA), go into effect - making data protection and disaster recovery a hybrid multicloud imperative," noted Lee Caswell, SVP of Product & Solutions Marketing at Nutanix.

Looking ahead, Nutanix says that finance service companies have not changed their priorities when assessing the suitability cloud providers. Flexibility, security, and data capabilities remain as important as they were last year. The study also notes the financial industrys greater emphasis on sustainability and cost compared with other sectors.

Many financial enterprises cited data access performance, security, and regulatory compliance as the driving factors for relocating applications to different infrastructures.

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Looking ahead, despite tighter regulatory restrictions imposed on the sector, its clear that even financial enterprises are seeking to benefit from the various cost, efficiency and sustainability advantages of hybrid cloud setups. Moreover, the cloud market, already worth $300 billion, is in for a healthy uptick as a result.

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Financial firms are increasingly turning to hybrid cloud - TechRadar

CoreWeave signs another 70MW hosting deal with Core Scientific – DatacenterDynamics

June 30, 2024 | Author: admin

CoreWeave is securing additional capacity at data centers owned by Core Scientific.

Cryptomine firm Core Scientific this week announced that GPU cloud provider CoreWeave is leasing a further 70MW from the company in a new 12-year deal.

Core Scientific will modify a total of 100MW of its owned infrastructure to deliver approximately 70MW to host CoreWeaves Nvidia GPUs for HPC operations.

Site modifications are expected to begin in the second half of 2024, with operational status anticipated in the second half of 2025.

The announcement comes after CoreWeave exercised its first option to contract additional infrastructure under the terms of the 200MW, 12-year hosting contract announced earlier this month. This deal adds 70MW to the originally contracted 200MW.

We are excited to build on our momentum and expand the scope of our HPC hosting business with significant additional infrastructure, said Adam Sullivan, Core Scientific CEO. The world is changing, and many data centers built in the last 20 years are not suitable to support future computing requirements. Our application-specific data centers will serve clients such as CoreWeave as they deploy next-generation chips with higher densities at scale.

Core Scientific said the deal will add an additional $1.225 billion in projected cumulative revenue over the 12-year contract timeline, in addition to the $3.5 billion previously predicted from the original deal. The new agreement with CoreWeave also provides opportunities for two renewal terms of five years each.

In addition to the 270MW already contracted and set to be delivered by H2 2025, CoreWeave retains options for a further 230MW at other Core Scientific sites.

Both CoreWeave and Core Scientific were founded in 2017 as crypto firms.

CoreWeave which counts Nvidia as an investor pivoted to a GPU cloud offering, providing access to GPUs for AI applications. Core Scientific, meanwhile has continued to focus on hosting cryptomining hardware for itself and others, and is increasingly starting to host AI-focused hardware.

The duo have worked together for several years. Core Scientific said it hosted thousands of CoreWeaves GPUs in its data centers from 2019 to 2022, and in March the companies announced CoreWeave was leasing 16MW of capacity from Core Scientific's Austin data center.

Under the 200MW deal announced earlier this month, Core Scientific said it will modify multiple existing, owned sites to host CoreWeaves Nvidia GPUs. The crypto-company intends to redeploy Bitcoin mining capacity from designated HPC sites to its other dedicated mining sites.

CoreScientific said that with 1.2GW of contracted power, the company is able to deliver nearly 500MW of HPC capacity. The company operates cryptomining data center campuses in Texas, North Dakota, Kentucky, Georgia, and North Carolina.

CoreWeave, meanwhile, has raised billions of dollars in equity and billions more in debt financing as it looks to become a major player in the AI cloud space. It has been on a major leasing spree in the last 18 months and previously said that it expects to operate 14 data centers by the end of 2023 and 28 by the end of 2024.

The company currently lists three data center regions on its website; US East in Weehawken, New Jersey; US West in Las Vegas, Nevada; and US Central in Chicago, Illinois, while its status page also lists a region in Reno. It has signed leasing deals with multiple providers across the US and is expanding into Europe.

Core Scientific filed for bankruptcy in late 2022 and emerged from proceedings earlier this year. This month it rejected an offer from CoreWeave to buy the company.

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CoreWeave signs another 70MW hosting deal with Core Scientific - DatacenterDynamics

Cloud Hosting

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Financial firms are increasingly turning to hybrid cloud – TechRadar

CoreWeave signs another 70MW hosting deal with Core Scientific – DatacenterDynamics

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