createLiveAI

🎓 MIT Tech Review AI

Feb 4, 2026

From guardrails to governance: A CEOs guide for securing agentic systems

Recent developments in AI security emphasize treating autonomous agents as powerful, semi-autonomous users, requiring strict boundary controls to mitigate risks. An actionable eight-step framework advocates for defining agent identity and scope by assigning each agent a specific, narrow role akin to a human user, ensuring they operate within constrained permissions aligned with their intended function, and prohibiting cross-tenant actions without explicit approval. This approach aligns with standards like Googles Secure AI Framework (SAIF) and NIST guidance, emphasizing the importance of transparency and accountability in managing agent capabilities. Implementing these controls involves establishing clear identity and scope protocols, such

Google AI Autonomous Systems +1

📄 Towards Data Science

Feb 4, 2026

How to Build Your Own Custom LLM Memory Layer from Scratch

A recent guide details the development of autonomous memory retrieval systems designed to enhance large language models (LLMs) by enabling dynamic and context-aware memory management. This approach involves constructing custom memory layers from scratch, allowing LLMs to efficiently access and utilize relevant information during inference, thereby improving performance and contextual understanding.

Autonomous Systems

Ethics

📄 AI News

Feb 4, 2026

How Cisco builds smart systems for the AI era

Cisco is advancing the deployment of AI both internally and in its product offerings by integrating machine learning and agentic AI to enhance service delivery and personalize user experiences. Its development of a shared AI fabric, built on validated compute and networking patterns, leverages high-performance GPUs and sophisticated integration between compute and network stacks to optimize model training and inference processes. This AI infrastructure underpins Ciscos focus on network automation, enabling automated configuration workflows and identity management that facilitate rapid, natural language-driven network deployments. By combining its expertise in enterprise networking with AI-driven automation, Cisco aims to deliver scalable, secure, and efficient

Machine Learning NLP

The Hacker News

Ethics

📄 The Hacker News

Feb 3, 2026

[Webinar] The Smarter SOC Blueprint: Learn What to Build, Buy, and Automate

The article highlights the ongoing challenge faced by security operations centers (SOCs) in managing increasingly complex and fragmented security tool stacks, leading to information overload and inefficiencies. Despite numerous vendors claiming to offer comprehensive coverage and AI-driven automation, many SOC teams remain overwhelmed, struggling to identify which tools deliver genuine value and improve threat detection and response.

Business

📄 AI News

Feb 3, 2026

Ronnie Sheth, CEO, SENEN Group: Why now is the time for enterprise AI to get practical

Ronnie Sheth, CEO of SENEN Group, emphasizes that the success of enterprise AI initiatives hinges critically on data quality, which Gartner estimates costs organizations an average of $12.9 million annually due to inefficiencies and missed opportunities. Despite increasing awareness of this issue, many companies still rush into AI adoption without adequate data readiness, leading to suboptimal outcomes and a lack of measurable impact. Sheth advocates for a more pragmatic and strategic approach, highlighting that organizations must prioritize establishing a solid data foundation before deploying AI solutions. This shift towards practical implementation aims to ensure that AI investments deliver tangible results, moving

General

📄 AI News

Feb 3, 2026

Apptio: Why scaling intelligent automation requires financial rigour

Greg Holmes, Field CTO for EMEA at Apptio, emphasizes that scaling intelligent automation effectively requires rigorous financial management, particularly through integrating FinOps capabilities to shift from reactive cost control to proactive value engineering. This approach enables technical teams to monitor resource consumption, such as cost per transaction or API call, from the outset, ensuring that automation projects are financially sustainable as they scale beyond pilot phases. Holmes highlights that many innovation projects fail due to financial opacity during pilots, which often mask future liabilities. He notes that while pilots may demonstrate time savings, they frequently rely on over-provisioned infrastructure, leading

The Hacker News

Ethics

📄 The Hacker News

Feb 3, 2026

Mozilla Adds One-Click Option to Disable Generative AI Features in Firefox

Mozilla has introduced a dedicated controls section in Firefox's desktop browser settings, enabling users to fully disable generative AI (GenAI) features. This new feature provides a centralized interface to block current and future AI functionalities, giving users greater privacy and control over AI integrations within the browser.

MarkTechPost

Technology

📄 MarkTechPost

Feb 2, 2026

The Statistical Cost of Zero Padding in Convolutional Neural Networks (CNNs)

Zero padding is a fundamental technique in convolutional neural networks (CNNs) that involves adding zero-valued pixels around the borders of an input image. This approach enables convolutional kernels to process edge pixels effectively and helps maintain the spatial dimensions of feature maps, preventing excessive shrinking after multiple convolutional layers. By controlling the amount of padding, researchers and engineers can preserve important spatial information and facilitate the construction of deeper, more complex neural network architectures. Recent analyses highlight the trade-offs associated with zero padding, particularly its impact on the statistical cost and computational efficiency of CNNs. While zero padding allows for better feature

Deep Learning

📄 Towards Data Science

Feb 2, 2026

Building Systems That Survive Real Life

Sara Nobrega highlights the evolving role of junior data scientists transitioning into AI engineering, emphasizing the importance of leveraging large language models (LLMs) as a bridge to DevOps practices. She underscores that mastering software engineering skills, particularly in system reliability and deployment, is crucial for data scientists to remain competitive in deploying AI solutions effectively in real-world environments.

📄 Towards Data Science

Feb 2, 2026

Silicon Darwinism: Why Scarcity Is the Source of True Intelligence

The article argues that future advancements in artificial intelligence will stem from operating within constrained environments rather than expanding data center size, emphasizing that true intelligence arises from scarcity rather than abundance. This perspective suggests that limiting resources and complexity can foster more efficient and adaptable AI systems, challenging the conventional focus on scaling up data and computational power for progress.

Business

📄 AI News

Feb 2, 2026

How SAP is modernising HMRCs tax infrastructure with AI

HMRC has partnered with SAP to modernize its core revenue management systems by replacing legacy infrastructure with a cloud-based, AI-enabled platform, emphasizing native machine learning and automation. This overhaul centers on the Enterprise Tax Management Platform (ETMP), which handles over 800 billion in annual tax revenue across multiple regimes, and aims to streamline operations by migrating to SAPs RISE with SAP cloud environment and deploying SAP Business Technology Platform and AI tools. The initiative addresses the challenges of fragmented on-premise systems by unifying data sets to enable effective machine learning and automated decision-making, while ensuring compliance with local data

Machine Learning