Good morning, it’s Friday. AI isn’t just writing your emails—it’s powering hyper-personalized phishing scams targeting executives. NVIDIA’s $3.28T valuation underscores its AI chip dominance, chatbots show potential but falter in real-world diagnostics, and KoBold Metals is using AI to transform the critical minerals supply chain.
Let’s dive in!
🤔 FRIDAY FACTS
By the end of 2025, 95% of retail customer interactions are expected to be AI-assisted. But what’s the first product ever sold using AI recommendations?
Stick around for the answer! 👇️
📧 PHISHING 2.0
AI-Generated Phishing Scams Target Executives with Hyper-Personalized Precision
The Recap: Corporate executives face a surge in hyper-personalized phishing attacks, fueled by AI’s ability to scrape vast online data and mimic authentic communication styles. As AI tools grow more advanced, cybersecurity experts warn of a rising tide of sophisticated scams that evade traditional defenses and carry costly consequences.
Highlights:
AI-powered phishing attacks leverage data scraped from online profiles to create convincing, personalized emails targeting executives.
British insurer Beazley and eBay report a sharp rise in cyberattacks using AI to mimic tone and style convincingly.
Generative AI tools make advanced phishing campaigns easier to execute, lowering the barrier for cybercriminals.
Researchers highlight AI’s role in crafting business email compromise scams, which have cost over $50 billion globally since 2013.
More than 90% of cyberattacks begin with phishing emails, and the average cost of a data breach rose to $4.9 million in 2024.
AI-generated scams evade detection by producing thousands of uniquely worded emails.
Security experts warn AI is not only scanning systems for vulnerabilities but also exploiting weaknesses in human behavior.
Forward Future Takeaways:
As AI-driven phishing attacks grow more sophisticated, businesses must adapt their defenses beyond traditional spam filters, focusing on AI-enhanced cybersecurity solutions and advanced threat detection systems. The rise of hyper-personalized scams underscores the urgent need for continuous employee training and robust data privacy policies to reduce vulnerability in an increasingly AI-powered threat landscape. → Read the full article here.
👾 FORWARD FUTURE ORIGINAL
Econ 10 | The Economics of Open-Source AI
In Econ 05 and Econ 06 I covered what is unique about software as opposed to the physical world. I fleetingly mentioned the concept of the ‘creative-commons free market of open source AI’. Why is it creative commons? How is it a free market? What exactly is open source and how does it matter to AI? Let’s explore these questions.
Let’s start with the very idea of open source. Software is written in a programming language. The resulting code - the set of instructions that define how the software should behave (such as with a cash machine (ATM) under what conditions it should trigger the dispensing of cash) - forms part of the ‘intellectual property’ of the people who built or own it.
Within the realm of intellectual property law, computer code has been deemed as something that is to be copyrighted rather than patented, just as other creative work in literary, educational and other spheres. This means, as hinted above, the builders or owners of the software retain the right to copy, distribute and otherwise make use of such code as they possess under the copyright.
However, the question of software code as copyrighted intellectual property took a different form early on. There arose this notion, and one that was spearheaded by stalwarts such as Richard Stallman, that code should be free to share, modify and reuse. This led, for example, to the concept of copyleft, as opposed to copyright of course, which provided for such freedoms, still within the legal framework of copyright law within the common law system. → Continue reading here.
🔬 RESEARCH PAPERS
CypherBench Boosts LLM Retrieval from Modern Knowledge Graphs
A new benchmark, CypherBench, aims to improve how large language models (LLMs) retrieve data from modern encyclopedic knowledge graphs like Wikidata. Researchers found that RDF-based graphs struggle with efficiency due to large schemas, overlapping relations, and complex identifiers that exceed LLM context windows. To address this, CypherBench introduces property graph views and uses Cypher queries for faster, more precise access to 7.8 million entities across 11 domains. The framework includes an RDF-to-property graph converter, a Cypher query generation pipeline, and new evaluation metrics—paving the way for better integration of knowledge graphs into AI systems. → Read the full paper here.
🛰️ NEWS
Looking Forward
🔬 Apheris Tackles AI Data Bottlenecks in Pharma: Apheris raised $8.25M to enable secure AI training on sensitive health data without moving it, winning clients like Roche and major pharma firms.
🧑⚕️ AI Oversight in Health Care Hinges on Trump: Brian Anderson’s Coalition for Health AI plans private-sector labs to vet AI tools, but critics warn of conflicts of interest and uneven safety standards.
🖥️ Samsung Unveils AI-Powered Monitors at CES: New Smart Monitor M9 boosts AI features and 4K upscaling, Odyssey OLED G8 debuts 27” 4K OLED gaming, and ViewFinity S8 offers a 37” productivity powerhouse.
🌊 xAI's Grok 3 Misses 2024 Launch: The anticipated release of xAI's Grok 3 model has been delayed, reflecting a broader trend of AI companies missing deadlines.
🤖 Meta Plans AI Social Media Surge with Virtual Users: Meta aims to populate platforms like Facebook with AI profiles featuring bios, photos, and content, sparking concerns over misinformation and content quality.
🚗 Lucid Motors introduces the Lucid Assistant: an in-vehicle voice assistant powered by SoundHound Chat AI, enabling drivers to control vehicle functions and access real-time information through natural speech.
🧰 TOOLBOX
AI Tools for Smarter Task Management, Goal Tracking, and Streamlined Coding
Draft | Task Management Simplified: Draft optimizes priorities, schedules tasks, and organizes categories using AI for seamless productivity and organization.
Mentor | Goal Planning Made Easy: Mentor helps users set goals, track progress, and stay motivated with personalized plans and analytics.
V0 | Coding & UI Streamlined: V0 streamlines web development with AI-driven UI generation, coding support, and interactive visualizations.
🤔 FRIDAY FACTS
The first product sold using AI recommendations? A book!
Amazon pioneered the use of AI for personalized recommendations in the late 1990s. Leveraging collaborative filtering, the platform began suggesting items based on users’ past purchases and browsing history. The result? Increased sales and a revolution in online shopping. Today, this technology fuels everything from movie suggestions to grocery delivery, proving that a good recommendation can go a long way—whether it's a bestseller or your nephew’s first novel.
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The Forward Future Team
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