Email remains a prime target for cyber criminals, with phishing identified as the leading attack vector, costing organizations an average of $4.45 million per breach. Former Google executives Cy Khormaee and Ryan Luo are tackling this issue with their startup AegisAI, which leverages artificial intelligence (AI) to enhance email security. AegisAI recently secured $13 million in seed funding, focusing on AI agents that analyze emails for intent, context, and user relationships, making them 20% more effective than traditional security measures. Unlike conventional tools, AegisAI identifies suspicious communications without significantly blocking legitimate emails, addressing a common industry challenge. Early clients, including crypto payment firm Mesh, have praised the platform’s effectiveness. As email security remains critical, with attackers utilizing advanced technologies, AegisAI is poised to impact the market significantly, backed by investors eager to capitalize on AI-driven solutions. The competitive landscape sees multiple startups vying for advancements in email security innovation.
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Leveraging AI to Combat Email Fraud and Scammers
Apple Trains AI to Navigate the Trump Era – POLITICO
Unlocking Apple’s AI Approach: A Deep Dive into Controversial Changes
Apple is redefining its AI guidelines, raising eyebrows across the tech community. Key changes revolve around how sensitive topics are addressed, impacting future interactions with users.
Key Takeaways:
- Evolving Guidelines: The latest updates shift how intolerance and discrimination are framed, moving “Diversity, Equity, and Inclusion (DEI)” to a “controversial” label.
- Shadowy Practices: Data annotators share concerns over the clarity and consistency of new instructions, fueling speculation about AI’s impartiality.
- Anticipated Launch: Apple is set to unveil its chatbot in 2026, a much-awaited development in the AI landscape, promising to challenge existing norms.
As industry professionals, it’s crucial to stay informed and engaged with these evolving narratives. Join the conversation about ethical AI and share your thoughts!
👉 Let’s explore more! Comment below and share this summary to keep the discussion alive!
Insights Unveiled: Discovering User Behavior Patterns with New Data
Recent data from Similarweb reveals that while ChatGPT is rapidly growing, Google remains the leading search engine. In August 2025, 95.3% of ChatGPT users also accessed Google, whereas only 14.3% of Google users visited ChatGPT. This trend indicates that AI chat tools like ChatGPT are being utilized as a complement to traditional search engines rather than as replacements.
Brodie Clark shared the findings on X, emphasizing that Google is still favored for its speed, reliability, and extensive search capabilities, despite the rise of AI tools. Research from Sparktoro supports this, showing that traditional search remains robust.
Users often turn to ChatGPT for specific tasks such as text summarization and content generation while relying on Google for broader searches and detailed information. Thus, current user behavior highlights a harmonious coexistence between AI platforms and traditional search engines, proving that both can effectively serve different needs in the digital landscape.
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Optimizing User Experience for AI Agents: Creating a Sense of Speed in Slow Interactions
Navigating the New Wave of Agentic Apps: Trusting the Wait
Agentic apps are revolutionizing how we interact with AI. These intelligent systems don’t just react—they actively perform complex tasks like data fetching and analysis. Yet, the excitement often dims when users encounter delays. Here’s what you need to know:
- The Reality of AI Speed: AI is intricate, juggling billions of parameters, and outcomes are probabilistic.
- User Experience Matters: Time isn’t just a metric; it shapes feelings. Delays impact attention and trust.
- Designing for Patience: Optimal strategies for handling waiting times include:
- 0-3 seconds: Seamless and engaging.
- 3-30 seconds: Features updates to maintain interest.
- 30+ seconds: Make the wait feel productive through engaging notifications.
Remember, not all waits are equal. Clear communication and visible progress are essential for fostering user trust.
Help reshape AI experiences! Share your thoughts and insights below.
Kennesaw State Researcher Pioneers Integration of Artificial Intelligence in Everyday Devices
Kennesaw State University researcher Bobin Deng is pioneering a new approach to artificial intelligence (AI) through a National Science Foundation grant. His research aims to make AI accessible on personal devices, eliminating the need for expensive supercomputers. By utilizing activation sparsity, Deng’s technique allows only a portion of AI model neurons to be active, significantly reducing memory usage and energy needs. This method can enhance efficiency when combined with existing techniques like pruning and quantization. His project focuses on deploying tiny machine-learning models that can support larger systems, making AI feasible for smartphones, drones, and industrial sensors. An open-source simulator will enable further exploration and refinement of this technology. This initiative aligns with KSU’s mission to advance innovation and prepare students for tech careers, showcasing the university as a leader in AI research. For more details, visit Kennesaw State University’s website.
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AI Halves Onboarding Time for New Enterprise Hire
Unlocking Developer Productivity with AI: Key Insights from Engineering Enablement
Welcome to this week’s Engineering Enablement newsletter! If you’re in the tech industry, you won’t want to miss the upcoming Enterprise Tech Leadership Summit, featuring insights from giants like Fidelity and Booking.com. I’ll be presenting and hosting a workshop there—come say hi!
Why AI Matters
- Onboarding Challenges: It can take months for new developers to reach full productivity, costing time and resources.
- AI as a Game Changer: Data from six multinational firms reveals that engineers using AI daily achieve their 10th pull request (PR) in just 49 days, nearly halving the average ramp-up time of 91 days for non-AI peers.
Tangible Benefits
- Daily AI users ship changes 1.3 times per week versus just 0.65 for those who don’t utilize AI.
- AI helps new hires grasp codebases and internal processes swiftly, accelerating their learning curve.
Join the conversation! Share your thoughts on AI’s role in tech onboarding and tag someone who could benefit from these insights!
Mace Group | Bridging the Future: How Data and AI are Transforming the Construction Industry
The construction industry is experiencing a digital revolution, driven by the need for efficiency, value, and certainty in increasingly complex projects. Mace Construct emphasizes the importance of digital integration, utilizing data and AI to move from reactive to predictive execution, enhancing collaboration among teams. Key trends include real-time digital collaboration, which minimizes fragmentation and boosts productivity by up to 30%. Mace’s Data Hub aggregates critical information across projects, enabling informed decision-making and minimizing risks. The use of AI and machine learning streamlines processes, allowing for precise performance tracking. Digital tools, including control rooms and field management systems, enhance quality assurance while promoting sustainability through material reuse strategies. As the industry shifts towards a data-led, AI-enabled future, firms must invest in skills that leverage technology effectively. Mace Construct is committed to transforming how construction is executed, creating smarter, more resilient urban environments through innovative practices and digital collaboration.
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Navigating AI Interfaces: The Power of ‘Do What I Mean’ Interconnectedness
Revolutionizing User Interfaces with AI: Intent Over Bureaucracy
David Galbraith explores how AI can transform user interfaces by shifting focus from complex command sequences to capturing user intent. Here’s a look at his innovative approach:
- AI Buttons: These are intuitive, allowing users to express desired outcomes simply—e.g., saying “remove clouds” instead of navigating menus.
- Semantic Interfaces: By facilitating user intent, AI can eliminate bureaucratic hurdles in software interactions.
- The DWIM Philosophy: Inspired by the concept of “Do What I Mean,” AI interfaces learn and adapt to user context, streamlining interaction.
Imagine a world where your devices understand you without the usual complexities! Whether in software or consumer hardware, optimizing for ease and expressiveness may reshape how we use technology.
Let’s spark a conversation on this transformative vision. How do you envision AI changing your tech interactions? Share your thoughts and help shape the future! #AI #UserInterface #Innovation
Google Cloud Unveils Conversational Commerce Agent for Enhanced, AI-Powered Personalized Shopping Experiences
Albertsons Companies partners with Google Cloud to introduce an AI-powered shopping assistant, “Conversational Commerce agent,” designed to enhance the grocery shopping experience. This innovative tool, built on Vertex AI, offers personalized product discovery, transforming how consumers shop across Albertsons’ various brand apps, including Safeway and Vons. With features like intelligent responses and natural conversations, it helps customers make informed choices, streamlines selection, and encourages the discovery of new products. As customers engage with the Ask AI tool, they often add more items to their carts, boosting sales. This collaboration underscores the shift toward personal, predictive, and effortless retail experiences driven by AI technology. Paul Tepfenhart from Google Cloud emphasizes the significant advantages retailers can gain through this AI integration, further establishing Albertsons as a leader in innovative grocery shopping solutions. The breakthrough aims to create meaningful customer interactions while improving overall engagement and revenue generation in a competitive market.
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Enhancing Security for AI Agents and LLM Workflows Without Relying on Secrets – Security Boulevard
In the article “Securing AI Agents and LLM Workflows Without Secrets,” Security Boulevard discusses strategies to enhance the security of artificial intelligence agents and Large Language Model (LLM) workflows. It emphasizes the importance of implementing robust security measures to safeguard sensitive data without relying solely on traditional secret management. The piece highlights the need for risk assessment, continuous monitoring, and adopting zero-trust principles in AI environments. By focusing on secure coding practices and efficient access controls, organizations can mitigate vulnerabilities and ensure the integrity of AI systems. Furthermore, it advises on leveraging encryption and secure APIs to protect data during transmission. The article concludes that a proactive approach to security posture not only fortifies AI applications but also helps maintain compliance with regulatory standards, ultimately fostering trust in AI-driven technologies. By following these guidelines, businesses can effectively protect their AI implementations and enhance their overall cybersecurity framework.
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