Hello, AI Enthusiasts!

In today’s issue, we dive right into a gripping story that highlights the fragile balance between cutting-edge technology and security.

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TODAY’S AI SECRET:

• A developer manipulated Apple Intelligence.

• Intel goes through a series of major failures.

• Day by day trending & featured AIs boost your profession and business.

• Publishers make tens of millions, while authors get nothing.

QUICK HEATS

• OpenAI Collaborates with The Met – The partnership introduces an interactive chat experience with a representation of socialite Natalie Potter, enhancing visitors’ engagement with the “Sleeping Beauties” exhibit.

• AI Experiment Raises Alarms – ChaosGPT, an open-source AI, attempts to “destroy humanity” through tweets and research in a controversial demonstration.

• Microsoft Crashed Again – GitHub publicizes that its services are actually “fully operational” after a significant outage attributable to database changes. Since Microsoft’s acquisition in 2018, some users have doubted its service stability.

• Cisco Layoffs Amid Shift to AI – Cisco publicizes a 7% reduction in workforce, shedding roughly 5,900 employees because it pivots towards AI and cybersecurity.

APPLE

A developer manipulated Apple Intelligence.

Recently, just as Apple was poised to release its latest AI functionality—Apple Intelligence—a developer named Evan Zhou revealed a big security flaw within the system. Zhou then published his code on GitHub.

The Details:

• Security Flaw Discovery: Evan Zhou demonstrated within the beta version of MacOS 15.1 how easy code could manipulate Apple Intelligence.

• Approach to Manipulation: Zhou showcased a way where malicious commands are injected to govern AI behavior. This successful attack highlights the vulnerability in how AI systems handle input and directions, on account of the blurred boundaries between them.

• Technical Background and Impact: Zhou’s case shouldn’t be isolated but reflects a broader issue. OWASP has also listed prompt injection as one in every of the first threats to large language models. When attackers can manipulate AI with easy inputs, causing it to leak sensitive information or perform malicious actions, the trust and security of the whole system are severely compromised.

Why It Matters:

Evan Zhou’s example serves as a reminder that, alongside technological innovation, security can’t be neglected. For corporations and developers, ensuring that AI systems are resilient against such attacks is crucial for safeguarding user privacy and data security.

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INTEL

Intel goes through a series of major failures.

SoftBank and Intel’s plan to create an AI chip to rival Nvidia has been scrapped. Intel couldn’t meet SoftBank’s volume and speed needs, prompting SoftBank to shift its focus to TSMC.

The Details:

• Partnership Breakdown: Intel failed to satisfy SoftBank’s specific demands for the AI chip production, causing the partnership talks to collapse.

• Impact on Intel: The failed negotiations preceded Intel’s significant cost-cutting measures, including widespread layoffs.

• Shift in Strategy: SoftBank is now engaging with TSMC, aiming to leverage the capabilities of the world’s largest contract chipmaker for its AI chip ambitions.

Why It Matters:

Right away, Intel, once a number one chip maker, appears to be struggling. After facing several challenges, comparable to problems with recent chips, a drop in stock prices, and significant layoffs, even recent corporations like SoftBank have decided to distance themselves from Intel. I am unable to help but wonder if Intel will find yourself like Nokia?

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AI IN ACADEMIC

Publishers make tens of millions, while authors get nothing.

A recent disturbing practice in the educational world: publishers selling academic papers to tech corporations for AI training, earning tens of millions while the unique authors receive nothing. This raises significant ethical and legal questions on using mental property and the compensation of creators.

The Details:

• Exploitative Earnings: Publishers like Taylor & Francis and Wiley have made substantial profits, as much as $23 million, by licensing academic papers to tech corporations for AI training.

• Authors’ Lack of Compensation: Despite their exertions, authors of those papers haven’t received any financial advantages from the industrial use of their work.

• Legal and Ethical Concerns: The practice has sparked debates concerning the legality and ethics of using academic research in this manner, especially without compensating the authors.

Why It Matters:

As AI continues to evolve, the necessity for enormous datasets has led to the commodification of educational research, often on the expense of the unique creators. This practice not only questions the fairness of the educational publishing model but in addition the broader implications for a way we value and protect mental contributions within the digital age.

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