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Big tech is prepping an explosive pivot to robotics

The ten most valuable tech firms in the world are all involved in developing technology for the robotics industry.

The next big thing in the technology industry appears to be consumer robotics and there could be massive implications for both Main Street and Wall Street. 

An analysis of the top ten tech firms in the world by market capitalization, their 2024 performance to-date, and what we’ve been able to glean about their current budgets indicates that big tech is ready to move beyond chatbots.

There are currently countless robots in the world. They’re used to build cars, stitch clothing, and even handle nuclear materials. But these specialized machines are purpose-built to perform specific tasks and typically not available or even useful to the average person.

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IBM’s new ‘Lightweight Engine’ could be a game changer for fintech

JP Morgan just rolled out ChatGPT to 60,000 employees, demonstrating the demand for generative AI in the financial services sector.

IBM recently launched a new “Lightweight Engine” for its WatsonX.ai service. While it’s primarily aimed at “enterprise,” it could serve as an on-ramp to secure, in-house generative AI deployment for smaller businesses looking to scale or mid-sized companies in burgeoning industries such as fintech.

The generative AI market is, inarguably, the primary catalyst behind the tech sector’s revenue growth in the first half of 2024. Just ten years prior, few could have predicted the sheer size and scope of a sector largely driven by the explosive popularity of large language models such as OpenAI’s ChatGPT and Anthropic’s Claude.

Prior to the launch of ChatGPT, experts in the AI and finance communities widely noted that large language models such as GPT-3 simply weren’t reliable or accurate enough for use in the world of finance or anywhere else where there’s no margin for error.

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German quantum breakthrough highlights need for particle physicists in crypto

German quantum breakthrough highlights need for particle physicists in crypto

Breakthrough quantum computing research out of Germany could lead to a revolution in particle physics with implications for finance, economics, and cryptocurrency. It might be time for firms in the crypto industry to add chief science officers and particle physicists to their portfolios. 

Much like the tech industry before it, crypto has bootstrapped itself on the virtue of its own feats of engineering and innovation. The engineering and innovation it took to invent blockchain and cryptocurrency are, arguably, analogous to the advent of personal computing and the internet.

Over the past 20 years, however, the tech industry has shifted towards hard science. Perhaps it’s time for crypto to follow suit.

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Biden’s Homeland Security team taps tech elite for AI defense board

The board includes the CEOs of Adobe, Alphabet, Anthropic, AMD, AWS, IBM, Microsoft, and Nvidia, as well as other business, civil rights, and academic leaders.

The United States Department of Homeland Security (DHS) recently announced the formation of an Artificial Intelligence Safety and Security Board composed of a veritable who’s who of tech CEOs, academics, and influential business leaders. 

Created under the direction of U.S. president Joseph Biden, the purpose of the new board is to advise DHS secretary Alejandro Mayorkas and the White House on matters related to artificial intelligence. Specifically, the board will “develop recommendations to help critical infrastructure stakeholders,” and “develop recommendations to prevent and prepare for AI-related disruptions to critical services that impact national or economic security, public health, or safety.”

CEOs from Adobe, Alphabet, Anthropic, AMD, AWS, Cisco, IBM, Microsoft, Nvidia, Delta Air Lines, Humane Intelligence, Occidental Petroleum, and Northropp Gruman make up the business sector of the board. They’re joined by academics from universities, civil rights and humanitarian institutions, the mayor of Seattle, Washington, and the governor of Maryland.

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IBM announces global Call for Code artificial intelligence hackathon winners

The global hackathon, now in its sixth year, gives participants access to advanced AI, cloud computing and blockchain technology.

The David Clark Cause, IBM, the United Nations Human Rights Office of the Commissioner and the Linux Foundation announced the winners of the 2023 Call for Code hackathon on Dec. 6.

Call for Code is the largest annual event of its kind, gathering participants from more than 180 nations who have produced a collective 24,000 applications to date, according to the David Clark Cause.

This year’s contest focused on solving “the most pressing global issues of our time” using available technologies, including IBM’s generative artificial intelligence (AI) service, watsonx. It included grand prizes awarded in three separate participant categories: developer, university and independent vendor/startup.

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IBM, Meta and others form ‘AI Alliance’ to advance AI development

In a joint statement, IBM and Meta outlined the AI Alliance’s objectives, emphasizing a commitment to safety, collaboration, diversity, economic opportunity, and universal benefits.

In the race for market supremacy among artificial intelligence (AI) firms, a coalition of technology leaders spearheaded by IBM and Meta established the AI Alliance.

In a joint statement, IBM and Meta outlined the AI Alliance’s objectives, emphasizing a commitment to safety, collaboration, diversity, economic opportunity, and universal benefits.

While numerous members endorse open-source development, it’s important to note that adherence to this model is not obligatory for membership.

“The progress we continue to witness in AI is a testament to open innovation and collaboration across communities of creators, scientists, academics, and business leaders.”

According to IBM and Meta, the AI Alliance will create a governing board and technical oversight committee focused on advancing AI projects and setting standards and guidelines.

“The AI Alliance brings together researchers, developers, and companies to share tools and knowledge that can help us all make progress whether models are shared openly or not,”

Looking to engage the academic community, the AI Alliance also includes several educational and research institutions, including CERN, NASA, Cleveland Clinic, Cornell University, Dartmouth, Imperial College London, University of California Berkeley, University of Illinois, University of Notre Dame, The University of Tokyo, and Yale University.

While Meta has advocated for open-source AI models and responsible development, the company opted to decentralize and streamline AI development by disbanding its responsible AI team in November.

Related: Meta’s AI boss says there’s an ‘AI war’ underway, and Nvidia is ‘supplying the weapons’

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IBM unveils new air-gapped cold storage solution for digital assets

The new system works a lot like a time delay safe for digital assets with a policy engine to broker communications.

IBM announced the launch of IBM Hyper Protect Offline Signing Orchestrator (OSO), an air-gapped cold storage solution for digital assets, on Dec.

Working with digital asset manager Metaco, an IBM partner and Ripple subsidiary, and tier-1 banks, IBM developed the end-to-end asset encryption service to address common vulnerabilities found in typical cold storage solutions.

Per an IBM blog post:

“When it comes to offline or physically air-gapped cold storage, there are limitations, including privileged administrator access, operational costs and errors and the inability to truly scale. All these limitations are due to one underlying factor—human interaction.”

Cold storage

IBM designed OSO to address these vulnerabilities by removing the manual functions of initiating and conducting transactions.

This, according to the blog post and accompanying research, prevents most common forms of insider attack including physical access, administrative manipulation, and coercion attacks.

Further ensuring OSO’s resilience to attack, digital assets can be placed in “air-gapped” storage container.

Securing blockchain transactions

Administrators managing cold storage solutions in a typical air-gapped paradigm usually have to hand-carry physical storage devices such as laptops or USB drives to offline hardware in order to sign transactions.

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IBM launches $500M fund to develop generative AI for enterprise

The new fund follows IBM’s participation in a $235M series D funding rounding in August for generative AI firm Hugging Face.

IBM announced the launch of a $500 million Enterprise AI Venture Fund on Nov. 7 that, according to the company, will be focused on “accelerating generative AI technology and research for the enterprise.”

Generative AI products for the consumer market, such as OpenAI’s ChatGPT and Google’s Bard, have dominated the newswaves in 2023.

IBM’s primarily focused on enterprise-level solutions for its generative AI products such as its Watson X platform and numerous cloud offerings.

According to Rob Thomas, a senior vice president at IBM, generative AI technologies will be a driving force for productivity and profitability throughout the next decade:

“AI is slated to unlock nearly $16 trillion in productivity by 2030. With the launch of the IBM Enterprise AI Venture Fund, we're opening another channel to harness the enormous potential of the AI revolution into tangible, positive outcomes for IBM and the companies we invest in.”

Details remain scarce as to exactly how IBM intends to invest its new $500 million AI Venture Fund. Per a company blog post, the fund will primarily focus on generative AI tech and will be used “to invest in a range of AI companies - from early-stage to hyper-growth startups.”

This fund follows IBM’s participation in a $235 million series D funding round in August for generative AI firm Hugging Face, a company known for its extensive transformer libraries — foundational pieces of technology for generative pretrained transformer (GPT) AI models.

Related: Biden AI executive order ‘certainly challenging’ for open-source AI — Industry insiders

With the recent slate of investments, including participating in machine learning security platform Hidden Layer’s series A round, IBM continues its ongoing trend of investing in enterprise AI startups while actively supporting the development of open source platforms, models, and protocols.

“With hundreds of open models on the Hugging Face hub, they are significantly boosting the open-source ecosystem,” said Hugging Face co-founder and CEO, Clem Delangue, in an IBM press release. “This is the reason why we wanted to have them join our series D round,” he continued, adding “I am convinced that they'll be able to accelerate their impact on AI with the IBM Enterprise AI Venture Fund."

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IBM’s new AI chip offers 22X speedup with ‘mind-blowing’ energy efficiency

The team’s already years into work on the next version of the potentially revolutionary NorthPole hardware.

IBM recently debuted a new prototype artificial intelligence (AI) chip purported to be both faster and far more energy efficient than any chip currently available. 

According to research published in Science Magazine on Oct. 19, the new chip, dubbed NorthPole, “achieves a 25 times higher energy metric” on a relevant benchmark, “and a 22 times lower time metric of latency.”

Ostensibly, this translates to the potential for post-GPU performance at a fraction of the cost in energy requirements.

Damien Querlioz, a nanoelectronics researcher at the University of Paris-Saclay in Palaiseau, described NorthPole’s energy efficiency as “mind-blowing,” in an article published on Nature.

Per the IBM Research team’s paper:

“NorthPole outperforms all prevalent architectures, even those that use more-advanced technology processes.”

One of the major impediments to improving AI processing is called the “von Neumann bottleneck.” Using currently available architecture, AI chips tend to have faster processing capabilities than the memory they require to run processes. As a result, latency is introduced whenever information is sent between the processing unit and random access memory.

This is especially true at “the edge,” where chips and data are stored together. Removing this bottleneck has long been considered by many experts to be the key to running powerful neural networks locally on devices.

According to IBM Research, the new prototype chip built in the company’s Alamaden, California laboratory bypasses the von Neumann bottleneck by, essentially, integrating the memory component onto the processing chip itself.

As the chip’s lead developer, Dharmendra Modha, puts it, NorthPole is “an entire network on a chip” that “forges a completely different path from the von Neumann architecture.”

“The NorthPole chip on a PCIe card.” Image source: IBM Research

The benchmark used to demonstrate the chip’s effectiveness, ResNet50, is a 50-layer neural network primarily used to test computer vision tasks such as image classification.

The NorthPole hardware’s reported results on this benchmark indicate that it could perform exceptionally well at associated tasks such as autonomous surgery, operation of self-driving cars and other vehicles, and numerous robotics-related endeavors.

IBM Research is already years into research on the next chip using the NorthPole architecture. According to the company blog, “this is just the start of the work for Modha on NorthPole.”

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IBM, Microsoft, others form post-quantum cryptography coalition

The coalition includes Google sibling company SandboxAQ and the University of Waterloo.

IBM Quantum and Microsoft have formed a coalition to tackle post-quantum cryptography alongside not-for-profit research tank MITRE, U.K.-based cryptography firm PQShield, Google sibling company SandboxAQ, and the University of Waterloo.

Post-quantum cryptography (PQC) addresses the potential threat posed by quantum computers of the future. Current cryptography schemes rely on mathematical problems to stymie decryption attempts.

Cracking or bypassing such encryption with a classical computer would be close to impossible. Some experts estimate that it would take a binary computer system roughly 300 trillion years to break a 1,024-bit or 2,048-bit RSA key.

RSA, named for the computer scientists who first discussed it, is largely considered the standard for encryption.

Theoretically speaking, however, a quantum computer with sufficient hardware and architecture should be able to break RSA and similar encryption schemes within a matter of weeks, days, or even hours.

According to a press release from MITRE:

“Preparing for a PQC transition includes developing standards for the algorithms; creating secure, reliable, and efficient implementations of those algorithms; and integrating the new post-quantum algorithms into cryptographic libraries and protocols.”

Technologies such as blockchain and cryptocurrency, which rely on mathematical encryption, could be particularly vulnerable to decryption attacks by the theoretical quantum computers of the future. However it's currently unclear how long it could be before such threats could come to fruition.

Related: Scientists warn the ‘quantum revolution’ may stagnate economic growth

One study, conducted in 2022, determined that it would take a quantum computer with 300 million qubits (a very generalized measure of the potential processing power of a quantum system) to crack the Bitcoin blockchain fast enough to do any damage. By comparison, today’s most advanced quantum computers average a little over 100 qubits.

However, per the architecture described in that paper, it’s possible that more advanced qubit arrangements, chipsets, and optimization algorithms could significantly change the calculus involved and drop the theoretical 300-million-qubit requirement exponentially. For this reason, the global technology community is turning to quantum-safe encryption.

The National Institute of Standards and Technology chose four proposed post-quantum encryption algorithms in 2022, CRYSTALS-Kyber, CRYSTALS-Dilithium, SPHINCS+, and Falcon as candidates for a PQC-safe encryption standard.

On Aug. 24, 2023, NIST announced that three of the algorithms had been accepted for standardization with the fourth, Falcon, expected to follow suit in 2024.

Now that the algorithms have been accepted and (mostly) standardized, the coalition is set to begin its mission of using the deep knowledge and hands-on experience amassed by its members to ensure key institutions, such as government, banking, telecommunications, and transportation services are able to transition from current to post-quantum encryption.

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