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Technology
Anthropic Artificial Intelligence DeepSeek NVIDIA OpenAI Technology

DeepSeek’s Rise: A Game-Changer in the AI Industry


January 27 marked a pivotal day for the artificial intelligence (AI) industry, with two major developments reshaping its future. First, Nvidia, the global leader in AI chips, suffered a historic loss of $589 billion in market value in a single day—the largest one-day loss ever recorded by a company. Second, DeepSeek, a Chinese AI developer, surged to the top of Apple’s App Store, surpassing ChatGPT. What makes DeepSeek’s success remarkable is not just its rapid rise but its ability to achieve high-performance AI with significantly fewer resources, challenging the industry’s reliance on expensive infrastructure.

DeepSeek’s Innovative Approach to AI Development

Unlike many AI companies that rely on costly, high-performance chips from Nvidia, DeepSeek has developed a powerful AI model using far fewer resources. This unexpected efficiency disrupts the long-held belief that AI breakthroughs require billions of dollars in investment and vast computing power. While companies like OpenAI and Anthropic have focused on expensive computing infrastructure, DeepSeek has proven that AI models can be both cost-effective and highly capable.

DeepSeek’s AI models perform at a level comparable to some of the most advanced Western systems, yet they require significantly less computational power. This approach could democratize AI development, enabling smaller companies, universities, and independent researchers to innovate without needing massive financial backing. If widely adopted, it could reduce the dominance of a few tech giants and foster a more inclusive AI ecosystem.

Implications for the AI Industry

DeepSeek’s success could prompt a strategic shift in the AI industry. Some companies may emulate its focus on efficiency, while others may continue investing in resource-intensive models. Additionally, DeepSeek’s open-source nature adds an intriguing dimension to its impact. Unlike OpenAI, which keeps its models proprietary, DeepSeek allows its AI to be downloaded and modified by researchers and developers worldwide. This openness could accelerate AI advancements but also raises concerns about potential misuse, as open-source AI can be repurposed for unethical applications.

Another significant benefit of DeepSeek’s approach is its potential to reduce the environmental impact of AI development. Training AI models typically consumes vast amounts of energy, often through large data centers. DeepSeek’s efficiency makes AI development more sustainable by lowering energy consumption and resource usage.

However, DeepSeek’s rise also brings challenges. As a Chinese company, it faces scrutiny over data privacy, security, and censorship. Like other AI developers, DeepSeek must navigate issues related to copyright and the ethical use of data. While its approach is innovative, it still grapples with industry-wide challenges that have plagued AI development in the past.

A More Competitive AI Landscape

DeepSeek’s emergence signals the start of a new era in the AI industry. Rather than a few dominant players controlling AI development, we could see a more competitive market with diverse solutions tailored to specific needs. This shift could benefit consumers and businesses alike, as increased competition often leads to better technology at lower prices.

However, it remains unclear whether other AI companies will adopt DeepSeek’s model or continue relying on resource-intensive strategies. Regardless, DeepSeek has already challenged conventional thinking about AI development, proving that innovation isn’t always about spending more—it’s about working smarter.

DeepSeek’s rapid rise and innovative approach have disrupted the AI industry, challenging the status quo and opening new possibilities for AI development. By demonstrating that high-performance AI can be achieved with fewer resources, DeepSeek has paved the way for a more inclusive and sustainable future. As the industry evolves, its impact will likely inspire further innovation, fostering a competitive landscape that benefits everyone.

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NVIDIA
cryptocurrency Cyber Fraud Facebook Investors NVIDIA

Facebook, Nvidia Push SCOTUS to Limit Investor Lawsuits

 




The US Supreme Court is set to take two landmark cases over Facebook and Nvidia that may rewrite the way investors sue the tech sector after scandals. Two firms urge the Court to narrow legal options available for investment groups, saying claims made were unrealistic.


Facebook's Cambridge Analytica Case

The current scandal is that of Cambridge Analytica, which allowed third-party vendors access to hundreds of millions of user information without adequate check or follow-up. Facebook reportedly paid over $5 billion to the FTC and SEC this year alone due to purportedly lying to the users as well as to the investors about how it uses data. Still, investor class-action lawsuits over the scandal remain, and Facebook is appealing to the Supreme Court in an effort to block such claims.

Facebook argues that the previous data risks disclosed were hypothetical and therefore should not have been portrayed as if they already had happened. The company also argues that forcing it to disclose all past data incidents may lead to "over disclosure," making the reports filled with data not helpful but rather confusing for investors. Facebook thinks disclosure rules should be flexible; if the SEC wants some specific incidents disclosed, it should create new regulations for that purpose.


Nvidia and the Cryptocurrency Boom

The second is that of Nvidia, the world's biggest graphics chip maker, which, allegedly, had played down how much of its 2017-2018 revenue was from cryptocurrency mining. When the crypto market collapsed, Nvidia was forced to cut its earnings forecast, which was an unexpected move for investors. Subsequently, the SEC charged Nvidia with $5.5 million for not disclosing how much of its revenue was tied to the erratic crypto market.

Investors argue that the statements from Nvidia were misleading due to the actual risks but point out that Nvidia responds by saying that such misrepresentation was not done out of malice. However, they argue that demand cannot be predicted in such an ever-changing market and so would lead to unintentional mistakes. According to them, the existing laws for securities lawsuits already impose very high standards to deter the "fishing expedition," where investors try to sue over financial losses without proper evidence. Nvidia's lawyers opine that relaxing these standards would invite more cases; henceforth the economy is harmed as a whole.


Possible Impact of Supreme Court on Investor Litigation


The Supreme Court will hear arguments for Facebook on November 6th, and the case for Nvidia is scheduled for Nov 13th. Judgments could forever alter the framework under which tech companies can be held accountable to the investor class. A judgement in favour of Facebook and Nvidia would make it tougher for shareholders to file a claim and collect damages after a firm has suffered a crisis. It could give tech companies respite but, at the same time, narrow legal options open to shareholders.

These cases come at a time when the trend of business-friendly rulings from the Supreme Court is lowering the regulatory authority of agencies such as the SEC. Legal experts believe that this new conservative majority on the court may be more open than ever to appeals limiting "nuisance" lawsuits, arguing that these cases threaten business stability and economic growth.

Dealing with such cases, the Court would decide whether the federal rules must permit private investors to enforce standards of corporate accountability or if such responsibility of accountability should rest primarily with the regulatory bodies like the SEC.


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NVIDIA
Big Tech Cyber Security CyberCrime Cyberhackers CyberThreat Facebook Meta NVIDIA

Big Tech Prioritizes Security with Zuckerberg at the Helm

 


Reports indicate that some of the largest tech firms are paying millions of dollars each year to safeguard the CEOs of their companies, with some companies paying more than others depending on the industry. There has been a significant increase in the costs relating to security for top executives, including the cost of monitoring at home, personal security, bodyguards, and consulting services, according to a Fortune report.

There was a lot of emphasis placed on securing high-profile CEOs, considering the risks they could incur, according to Bill Herzog, CEO of LionHeart Security Services. Even though it has been two months since Meta cut thousands of jobs on its technical teams, its employees are still feeling the consequences. 

The Facebook core app is supported by employees in many ways, from groups to messaging, and employees who have spent weeks redistributing responsibilities left behind by their departed colleagues, according to four current and former employees who were asked to remain anonymous to speak about internal issues. 

Many remaining employees are likely adjusting to new management, learning completely new roles, and - in some cases - just trying to get their heads around what is happening. The cost of security services offered by LionHeart Security Services is $60 per hour or more, which could represent an annual budget of over $1 million for two guards working full-time. 

In terms of personal security for Mark Zuckerberg, Meta has invested $23.4 million in 2023, breaking the lead among the competitors. The amount of $9.4 million is comprised of direct security costs, while a pre-tax allowance of $14 million is reserved for additional security-related expenses that may arise in the future. 

The investment by Alphabet Inc. in 2023 will amount to about $6.8 million, while Tesla Inc. has paid $2.4 million for the security services of its CEO Elon Musk, in 2023. Additionally, other technology giants, such as NVIDIA Corporation and Apple Inc. have also invested heavily to ensure the safety of their CEOs, with the two companies spending $2.2 million and $820,309, respectively, in 2023. 

In recent years, tech companies have become more aware of the importance of security for their top executives. Due to the increasing risks associated with high-profile clients, the costs of these services have increased as a result of the increase in demand. The fact that these organizations have invested significant amounts of money into security measures over the years makes it clear that they place a high level of importance on the safety of their leaders, which is reflected in their significant investments in these measures. 

The article also highlights the potential risks that are involved in leading a major tech company in today's world, due to technological advancements. Since Zuckerberg joined Meta's platforms over a decade ago, he has faced increasing scrutiny to prove he is doing what is necessary to ensure the safety of children on its platforms. Facebook's founder, Mark Zuckerberg, apologized directly to parents who have complained their children are suffering harm due to content on Meta's platforms, including Facebook and Instagram, during a recent hearing of the Senate Judiciary Committee. 

This apology came after intense questioning from lawmakers about Meta’s efforts to protect children from harmful content, including non-consensual explicit images. Despite Meta’s investments in safety measures, the company continues to face criticism for not doing enough to prevent these harms. Zuckerberg's apology reflected both an acknowledgement of these issues and his willingness to accept responsibility for them. 

However, it also highlighted the ongoing challenges Meta faces in addressing safety concerns in the future. In a multifaceted and complex answer to the question of whether Mark Zuckerberg should step down as Meta's CEO, there are many issues to consider. It is important to point out that there are high ethical concerns and controversy surrounding his conduct that have seriously compromised the public's trust in the leadership of the country. 

Meta has been well positioned for success due to his visionary approach and deep insight into the company which has greatly contributed to the success of the organization. What is important in the end is what will benefit the company's future, that is what matters in the end. However, if Zuckerberg can demonstrate that he is in fact trying to address ethical issues, as well as make the platform more transparent, and if he can prove it well and truly, then he might do well to keep the position at Meta, despite the fears that he may lose it. 

The business may require a change in leadership if these issues persist, which will lead to the restoration of trust, which will enable the business to maintain a more sustainable and ethical outlook.
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Technology
AI energy efficiency brain-inspired computing cryptocurrency energy consumption IBM Intel Loihi 2 chip neuromorphic computing NorthPole chip NVIDIA rising energy demands SpiNNcloud Systems Technology

Could Brain-Like Computers Be a Game Changer in the Tech Industry?

 

Modern computing's demand for electricity is growing at an alarming pace. By 2026, energy consumption by data centers, artificial intelligence (AI), and cryptocurrency could potentially double compared to 2022 levels, according to a report from the International Energy Agency (IEA). The IEA estimates that by 2026, these sectors' energy usage could be equivalent to Japan's annual energy consumption.

Companies like Nvidia, which produces chips for most AI applications today, are working on developing more energy-efficient hardware. However, another approach could be to create computers with a fundamentally different, more energy-efficient architecture.

Some companies are exploring this path by mimicking the brain, an organ that performs more operations faster than conventional computers while using only a fraction of the power. Neuromorphic computing involves electronic devices imitating neurons and synapses, interconnected similarly to the brain's electrical network.

This concept isn't new; researchers have been investigating it since the 1980s. However, the rising energy demands of the AI revolution are increasing the urgency to bring this technology into practical use. Current neuromorphic systems mainly serve as research tools, but proponents argue they could greatly enhance energy efficiency.

Major companies like Intel and IBM, along with several smaller firms, are pursuing commercial applications. Dan Hutcheson, an analyst at TechInsights, notes, "The opportunity is there waiting for the company that can figure this out... it could be an Nvidia killer." In May, SpiNNcloud Systems, a spinout from the Dresden University of Technology, announced it would begin selling neuromorphic supercomputers and is currently taking pre-orders.

Hector Gonzalez, co-chief executive of SpiNNcloud Systems, stated, "We have reached the commercialization of neuromorphic supercomputers ahead of other companies." Tony Kenyon, a professor at University College London, adds, "While there still isn’t a killer app... there are many areas where neuromorphic computing will provide significant gains in energy efficiency and performance, and I’m sure we’ll start to see wide adoption as the technology matures."

Neuromorphic computing encompasses various approaches, from a brain-inspired design to near-total simulation of the human brain, though we are far from achieving the latter. Key differences from conventional computing include the integration of memory and processing units on a single chip, which reduces energy consumption and speeds up processing.

Another common feature is an event-driven approach, where imitation neurons and synapses activate only when they have something to communicate, akin to the brain's function. This selective activation saves power compared to conventional computers that are always on.

Additionally, while modern computers are digital, neuromorphic computing can also be analog, relying on continuous signals, which is useful for analyzing real-world data. However, most commercially focused efforts remain digital for ease of implementation.

Commercial applications of neuromorphic computing are envisioned in two main areas: enhancing energy efficiency and performance for AI applications like image and video analysis, speech recognition, and large-language models such as ChatGPT, and in "edge computing" where data is processed in real-time on connected devices under power constraints. Potential beneficiaries include autonomous vehicles, robots, cell phones, and wearable technology.

However, technical challenges persist, particularly in developing software for these new chips, which requires a completely different programming style from conventional computers. "The potential for these devices is huge... the problem is how do you make them work," Hutcheson says, predicting that it could take one to two decades before neuromorphic computing's benefits are fully realized. Cost is another issue, as creating new chips, whether using silicon or other materials, is expensive.

Intel's current prototype, the Loihi 2 chip, is a significant advancement in neuromorphic computing. In April, Intel announced Hala Point, a large-scale neuromorphic research system comprising 1,152 Loihi 2 chips, equating to over 1.15 billion neurons and 128 billion synapses—about the neuron capacity of an owl brain. Mike Davies, director of Intel's neuromorphic computing lab, says Hala Point shows real viability for AI applications and notes rapid progress on the software side.

IBM's latest brain-inspired prototype chip, NorthPole, is an evolution of its previous TrueNorth chip. According to Dharmendra Modha, IBM's chief scientist of brain-inspired computing, NorthPole is more energy and space efficient and faster than any existing chip. IBM is now working to integrate these chips into a larger system, with Modha highlighting that NorthPole was co-designed with software to fully exploit its architecture from the outset.

Other smaller neuromorphic companies include BrainChip, SynSense, and Innatera. SpiNNcloud’s supercomputers commercialize neuromorphic computing developed at TU Dresden and the University of Manchester under the EU’s Human Brain Project. This project has produced two research-purpose supercomputers: SpiNNaker1 at Manchester, operational since 2018 with over one billion neurons, and SpiNNaker2 at Dresden, capable of emulating at least five billion neurons and currently being configured. SpiNNcloud's commercial systems are expected to emulate at least 10 billion neurons.

According to Professor Kenyon, the future will likely feature a combination of conventional, neuromorphic, and quantum computing platforms, all working together.
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Technology
Apple CyberCrime Cybersecurity Cyberthreats Cyerattacks Data Safety iPhones Meta NVIDIA Technology

Nvidia Climbs to Second Place in Global Market Value, Surpassing Apple

 


This month, Nvidia has achieved a historic achievement by overtaking Apple to become the world's second most valuable company, a feat that has only been possible because of the overwhelming demand for its advanced chips that are used to handle artificial intelligence tasks. A staggering $1.8 trillion has been added to the market value of the Santa Clara, California-based company's shares over the past year, increasing its market value by a staggering 147% this year. 

Nvidia has achieved a market capitalisation of over $3 trillion as a result of this surge, becoming the first semiconductor company to achieve this milestone. The value of Nvidia's shares has skyrocketed over the past few years, making it the second most valuable company in the world and larger than Apple, thanks to its surge in value. As a consequence of the excitement regarding artificial intelligence, which is largely based on Nvidia chips, the company has seen its shares rise dramatically over the past few years.

The popularity of the company has resulted in it becoming the largest company in Silicon Valley, which has led it to replace Apple, which has seen its share price fall due to concerns regarding iPhone sales in China and other concerns. Several weeks from now, Nvidia will be split ten times for ten shares, a move that could greatly increase the appeal of its stock to investors on a personal level. Nvidia’s surge over Apple’s market value signals a shift in Silicon Valley, where the co-founded company by Steve Jobs has dominated the field since the iPhone was launched in 2007. While Apple gained 0.78 per cent, the world’s most valuable company, Microsoft gained 1.91 per cent in value. 

As a result of the company’s graphics processing units fuelling a boom in artificial intelligence (AI), Nvidia’s rally continues an extraordinary streak of gains for the company. There has been a 260 per cent increase in revenue for the company in recent years, as tech titans such as Microsoft, Meta, Google, and Amazon race to implement artificial intelligence. 

Last month, Nvidia announced a 10-for-1 stock split as a way of making stock ownership more accessible to employees and investors. In the first half of this year, Nvidia shares have more than doubled in value after almost tripling in value in 2023. With the implementation of the split on Friday, the company will be able to appeal to a larger number of small-time investors, as the company's shares will become even more attractive. 

As a consequence of Microsoft, Meta Platforms, and Alphabet, all of these major tech companies are eager to enhance their artificial intelligence capabilities, which is why Nvidia's stock price has surged 147% in 2024. According to recent revenue estimates, the company's stock has gained close to $150 million in market capitalisation in one day, which is more than the entire market capitalization of AT&T. As well as a 4.5% increase in the PHLX chip index, many companies have benefited from the current optimism surrounding artificial intelligence, including Super Micro Computer, which builds AI-optimized servers using Nvidia chips. 

During his visit to the Computex tech fair in Taiwan, former Taipei resident Jensen Huang, chairman & CEO of Nvidia, received extensive media coverage that highlighted both his influence on the company's growing importance as well as his association with the event. Compared to Apple, there are challenges facing Apple due to weak demand for iPhones in China and stiff competition from its Chinese competitors. According to some analysts, Apple misses out on incorporating AI features compared to other tech giants because the company has been so slow in incorporating them. 

According to LSEG data, Nvidia's stock trades today at 39 times expected earnings, but the stock is still considered less expensive than a year ago, when the stock traded at more than 70 times expected earnings, indicating it's less expensive than it used to be.
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Are GPUs Ready for the AI Security Test?

 


As generative AI technology gains momentum, the focus on cybersecurity threats surrounding the chips and processing units driving these innovations intensifies. The crux of the issue lies in the limited number of manufacturers producing chips capable of handling the extensive data sets crucial for generative AI systems, rendering them vulnerable targets for malicious attacks.

According to recent records, Nvidia, a leading player in GPU technology, announced cybersecurity partnerships during its annual GPU technology conference. This move underscores the escalating concerns within the industry regarding the security of chips and hardware powering AI technologies.

Traditionally, cyberattacks garner attention for targeting software vulnerabilities or network flaws. However, the emergence of AI technologies presents a new dimension of threat. Graphics processing units (GPUs), integral to the functioning of AI systems, are susceptible to similar security risks as central processing units (CPUs).


Experts highlight four main categories of security threats facing GPUs:


1. Malware attacks, including "cryptojacking" schemes where hackers exploit processing power for cryptocurrency mining.

2. Side-channel attacks, exploiting data transmission and processing flaws to steal information.

3. Firmware vulnerabilities, granting unauthorised access to hardware controls.

4. Supply chain attacks, targeting GPUs to compromise end-user systems or steal data.


Moreover, the proliferation of generative AI amplifies the risk of data poisoning attacks, where hackers manipulate training data to compromise AI models.

Despite documented vulnerabilities, successful attacks on GPUs remain relatively rare. However, the stakes are high, especially considering the premium users pay for GPU access. Even a minor decrease in functionality could result in significant losses for cloud service providers and customers.

In response to these challenges, startups are innovating AI chip designs to enhance security and efficiency. For instance, d-Matrix's chip partitions data to limit access in the event of a breach, ensuring robust protection against potential intrusions.

As discussions surrounding AI security evolve, there's a growing recognition of the need to address hardware and chip vulnerabilities alongside software concerns. This shift reflects a proactive approach to safeguarding AI technologies against emerging threats.

The intersection of generative AI and GPU technology highlights the critical importance of cybersecurity in the digital age. By understanding and addressing the complexities of GPU security, stakeholders can mitigate risks and foster a safer environment for AI innovation and adoption.


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Nvidia Unveils Latest AI Chip, Promising 30x Faster Performance

 

Nvidia, a dominant force in the semiconductor industry, has once again raised the bar with its latest unveiling of the B200 "Blackwell" chip. Promising an astonishing 30 times faster performance than its predecessor, this cutting-edge AI chip represents a significant leap forward in computational capabilities. The announcement was made at Nvidia's annual developer conference, where CEO Jensen Huang showcased not only the groundbreaking new chip but also a suite of innovative software tools designed to enhance system efficiency and streamline AI integration for businesses. 

The excitement surrounding the conference was palpable, with attendees likening the atmosphere to the early days of tech presentations by industry visionaries like Steve Jobs. Bob O'Donnell from Technalysis Research, who was present at the event, remarked, "the buzz was in the air," underscoring the anticipation and enthusiasm for Nvidia's latest innovations. 

One of the key highlights of the conference was Nvidia's collaboration with major tech giants such as Amazon, Google, Microsoft, and OpenAI, all of whom expressed keen interest in leveraging the capabilities of the new B200 chip for their cloud-computing services and AI initiatives. With an 80% market share and a track record of delivering cutting-edge solutions, Nvidia aims to solidify its position as a leader in the AI space. 

In addition to the B200 chip, Nvidia also announced plans for a new line of chips tailored for automotive applications. These chips will enable functionalities like in-vehicle chatbots, further expanding the scope of AI integration in the automotive industry. Chinese electric vehicle manufacturers BYD and Xpeng have already signed up to incorporate Nvidia's new chips into their vehicles, signalling strong industry endorsement. 

Furthermore, Nvidia demonstrated its commitment to advancing robotics technology by introducing a series of chips specifically designed for humanoid robots. This move underscores the company's versatility and its role in shaping the future of AI-powered innovations across various sectors. Founded in 1993, Nvidia initially gained recognition for its graphics processing chips, particularly in the gaming industry. 

However, its strategic investments in machine learning capabilities have propelled it to the forefront of the AI revolution. Despite facing increasing competition from rivals like AMD and Intel, Nvidia remains a dominant force in the market, capitalizing on the rapid expansion of AI-driven technologies. As the demand for AI solutions continues to soar, Nvidia's latest advancements position it as a key player in driving innovation and shaping the trajectory of AI adoption in the business world. With its track record of delivering high-performance chips and cutting-edge software tools, Nvidia is poised to capitalize on the myriad opportunities presented by the burgeoning AI market.
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NVIDIA's Dominance in Shaping the Digital World

 


NVIDIA, a global technology powerhouse, is making waves in the tech industry, holding about 80% of the accelerator market in AI data centres operated by major players like AWS, Google Cloud, and Microsoft Azure. Recently hitting a monumental $2 trillion market value, NVIDIA's stock market soared by $277 billion in a single day – a historic moment on Wall Street.

In a remarkable financial stride, NVIDIA reported a staggering $22.1 billion in revenue, showcasing a 22% sequential growth and an astounding 265% year-on-year increase. Colette Kress, NVIDIA's CFO, emphasised that we are at the brink of a new computing era.

Jensen Huang, NVIDIA's CEO, highlighted the integral role their GPUs play in our daily interactions with AI. From ChatGPT to video editing platforms like Runway, NVIDIA is the driving force behind these advancements, positioning itself as a leader in the ongoing industrial revolution.

The company's influence extends to generative AI startups like Anthropic and Inflection, relying on NVIDIA GPUs, specifically RTX 5000 and H100s, to power their services. Notably, Meta's Mark Zuckerberg disclosed plans to acquire 350K NVIDIA H100s, emphasising NVIDIA's pivotal role in training advanced AI models.

NVIDIA is not only a tech giant but also a patron of innovation, investing in over 30 AI startups, including Adept, AI21, and Character.ai. The company is actively engaged in healthcare and drug discovery, with investments in Recursion Pharmaceuticals and its BioNeMo AI model for drug discovery.

India has become a focal point for NVIDIA, with promises of tens of thousands of GPUs and strategic partnerships with Reliance and Tata. The company is not just providing hardware; it's actively involved in upskilling India's talent pool, collaborating with Infosys and TCS to train thousands in generative AI.

Despite facing GPU demand challenges last year, NVIDIA has significantly improved its supply chain. Huang revealed plans for a new GPU range, Blackwell, promising enhanced AI compute performance, potentially reducing the need for multiple GPUs. Additionally, the company aims to build the next generation of AI factories, refining raw data into valuable intelligence.

Looking ahead, Huang envisions sovereign AI infrastructure worldwide, making AI-generation factories commonplace across industries and regions. The upcoming GTC conference in March 2024 is set to unveil NVIDIA's latest innovations, attracting over 300,000 attendees eager to learn about the next generation of AI.

To look at the bigger picture, NVIDIA's impact extends far beyond its impressive financial achievements. From powering AI startups to influencing global tech strategies, the company is at the forefront of shaping the future of technology. As it continues to innovate, NVIDIA remains a key player in advancing AI capabilities and fostering a new era of computing.


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