Gemini by Google

Gemini is Google’s next-generation family of AI models designed to deliver powerful, multimodal intelligence across text, code, images, audio, and video. Developed by Google DeepMind, Gemini combines the strengths of large language models with advanced reasoning and understanding, making it suitable for everything from creative content generation to complex problem-solving and enterprise applications. With versions like Gemini 1.5 and the lightweight Gemini Flash, the platform offers flexible deployment options via Google AI Studio and Vertex AI, empowering developers and businesses to build intelligent solutions at scale.

Master LLM Prompt Engineering: 5 Expert Techniques to Boost AI Output Quality in 2025

The Complete Prompt Engineering Guide 2025: Master AI Techniques That Boost Output Quality by 340%

Ravi Jain
"Master LLM Prompt Engineering: 5 Expert Techniques" by AI Engineering Expert, focuses on the critical importance of prompt engineering for optimizing Large Language Model (LLM) performance. It introduces prompt engineering as the art and science of crafting effective instructions to guide AI models, highlighting its benefits like increased productivity, enhanced accuracy, and cost optimization. The article details five specific techniques: co-creating prompts with AI, implementing AI self-evaluation, structuring responses with examples, breaking down complex tasks, and leveraging AI reasoning for optimization. Finally, it promotes Technijian's AI consulting services, positioning them as experts in helping businesses implement these advanced prompt engineering strategies. ... Read More
The Ultimate AI Research Combo: How NotebookLM's Audio Overviews in Gemini with Deep Research Transform Content Creation

The Ultimate AI Research Combo: How NotebookLM’s Audio Overviews in Gemini with Deep Research Transform Content Creation

Ravi Jain
Google's AI-powered research tools, NotebookLM and Gemini, highlighting their Audio Overviews feature. This feature converts research sources into podcast-style discussions hosted by virtual AI presenters, aiming to make information consumption more engaging and efficient. The document outlines the strengths and use cases for each platform, with NotebookLM excelling in source-specific academic research and Gemini specializing in broad, comprehensive topic exploration through Deep Research capabilities. Ultimately, the text presents these tools as a game-changer for content creation, academic work, and business analysis, offering enhanced accessibility, efficiency, and engagement in processing information. ... Read More
AI data security crisis infographic showing 99% of organizations with exposed sensitive data and cybersecurity threats in 2025

AI Data Breach Statistics 2025

Ravi Jain
"AI Data Security Crisis 2025," explains that while AI tools offer significant productivity gains, they also pose a substantial risk, creating the largest data security crisis in corporate history. Ninety-nine percent of organizations have sensitive data exposed to AI tools, making data breaches a certainty rather than a possibility. This vulnerability stems from AI's insatiable appetite for data and its ability to access sensitive information beyond its intended scope, leading to both human-to-machine and machine-to-machine risks. The article stresses the urgency of implementing a three-pillar strategy for AI data security: blast radius reduction, continuous monitoring and governance, and leveraging AI-powered security solutions. It also outlines a comprehensive implementation roadmap, emphasizing the need for professional technical support to assess vulnerabilities, implement tailored solutions, and provide ongoing monitoring and compliance management. The text concludes by asserting that investing in AI data security is crucial, as the cost of inaction far outweighs the investment in protective measures. ... Read More
AI security threats

How Cybercriminals Are Weaponizing Misconfigured AI Systems

Ravi Jain
"Securing AI: A Guide to Protecting Artificial Intelligence Systems," explores the escalating threats posed by cybercriminals targeting misconfigured AI systems. It details how attackers exploit vulnerabilities in AI infrastructure, such as exposed Jupyter notebooks and weak authentication, to launch sophisticated, AI-powered attacks like prompt injection and model poisoning. The guide outlines various attack vectors across Linux and Windows environments and emphasizes the long-term impact of compromised AI models. Finally, it presents comprehensive detection and prevention strategies, including infrastructure hardening, AI-specific security measures, and enterprise security frameworks, along with services offered by Technijian to address these critical security challenges. ... Read More
Google AI search ads

The Truth Behind Google’s AI Search Ads: Marketing Innovation or User Experience Compromise?

Ravi Jain
The sources discuss Google's integration of advertisements into its new AI-powered search features, AI Overviews and AI Search Mode. This shift places ads below AI-generated summaries but above organic results, raising questions about user experience versus revenue generation. While Google claims internal data shows these ads are helpful, the lack of transparency regarding their research methodology is a significant concern. The sources also explore the impact on digital marketing, creating both opportunities for increased visibility and challenges like reduced organic reach and increased competition. ... Read More