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The "10 blue links" are fading. In the age of SearchGPT and Google SGE, marketing is no longer about keywords it's about authority, velocity, and user intent.To rank and convert in 2026, you need a stack that covers content, video, and analytics. Here are the top 10 AI marketing tools driving growth this year.1. Surfer AIBest for: SEO Content OptimizationSurfer remains the gold standard for on-page SEO. Its latest AI engine writes entire articles that are pre-optimized to rank, analyzing over 500 signals from top-ranking pages to ensure your content satisfies the "Answer Engine" algorithms.2. JasperBest for: Enterprise Brand VoiceUnlike generic ChatGPT, Jasper allows companies to upload their brand style guides. It ensures that every piece of content—from emails to blog posts—sounds exactly like your brand, maintaining consistency across large teams.3. Canva Magic StudioBest for: Visual Content CreationCanva’s AI suite now includes "Magic Switch" (instantly resizing content for all social platforms) and "Magic Media" (text-to-video generation), allowing marketers to create high-end assets without a design team.4. VidIQBest for: YouTube GrowthVidIQ uses AI to analyze YouTube’s algorithm. It predicts which video titles and thumbnails will get the highest Click-Through Rate (CTR) before you even hit record, and generates optimized descriptions and tags instantly.5. MarketMuseBest for: Content Strategy & AuthorityMarketMuse audits your entire website to find "content gaps." It tells you exactly what topics you are missing if you want to be considered an authority in your niche by Google’s E-E-A-T standards.6. WriterBest for: Corporate Governance & AccuracyWriter is the AI for adults in the room. It checks content not just for grammar, but for legal compliance, factual accuracy, and prohibited terms, making it safe for regulated industries like finance and healthcare.7. HubSpot AIBest for: CRM & Marketing AutomationHubSpot’s "Breeze" AI agents can scour your CRM to draft personalized emails to prospects, update deal stages automatically, and even generate blog posts based on customer questions logged by your support team.8. Albert.aiBest for: Autonomous Ad OptimizationAlbert connects to your paid search and social accounts (Google Ads, Meta). It autonomously tests thousands of ad variations, allocating budget to the best performers and pausing losers 24/7, far faster than a human media buyer.9. FraseBest for: Answer Engine Optimization (AEO)Frase helps you structure content for the "Zero-Click" world. It identifies the questions users are asking and helps you format your answers so they are picked up by AI summaries in Google SGE and Perplexity.10. Originality.aiBest for: Fact-Checking & AI DetectionIn a world of spam, trust is currency. Originality.ai verifies that your content is factually accurate and scans it to ensure it doesn't look like low-effort spam, protecting your site from Google’s "Helpful Content" penalties.

The only way to stop an AI-driven attack is with an AI-driven defense. As hackers utilize generative AI to create polymorphic malware and deepfake social engineering, legacy firewalls are no longer enough.Here are the top 10 AI cybersecurity tools that every CISO and IT manager needs to know about in 2026.1. DarktraceCategory: Self-Learning Network DefenseDarktrace uses an "Enterprise Immune System" approach. It installs on your network and learns what "normal" behavior looks like for every user and device. When it detects an anomaly—like a marketing laptop accessing a finance server at 3 AM—it autonomously interrupts the connection.2. CrowdStrike FalconCategory: Endpoint ProtectionPowered by "Charlotte AI," CrowdStrike leverages massive global telemetry to predict threats. It allows security analysts to ask plain English questions about their network status and can identify malware signatures that haven't even been cataloged yet.3. TessianCategory: Email SecurityTessian moves beyond checking for typos. It analyzes the context of email communications. If a CEO sends an urgent wire transfer request but the tone doesn't match their historical pattern, Tessian flags it as a potential deepfake text attack.4. Vectra AICategory: Network Threat DetectionVectra specializes in hunting down attackers who have already breached the perimeter. It analyzes network traffic to find "behavioral" evidence of a spy, such as lateral movement or data exfiltration.5. SentinelOneCategory: Automated Response & RollbackSentinelOne is famous for its remediation. If ransomware manages to encrypt a computer, SentinelOne’s AI can kill the process and actually reverse the file changes, restoring the computer to its pre-infected state instantly.6. PindropCategory: Deepfake Voice DetectionWith voice cloning fraud on the rise in 2026, Pindrop is essential for call centers and finance teams. It analyzes audio at a micro-level to determine if a voice on the phone is human or synthetic.7. Tenable OneCategory: Vulnerability ManagementTenable uses predictive AI to tell you not just which vulnerabilities exist, but which ones are actually likely to be exploited in the wild, helping IT teams prioritize the 1% of patches that actually matter.8. Abnormal SecurityCategory: Behavioral Email DefenseAbnormal focuses on Business Email Compromise (BEC). It builds a sociogram of your organization to understand relationships and vendors, blocking invoices that look legitimate but come from compromised vendor accounts.9. WizCategory: Cloud Security (CNAPP)Wiz scans your entire cloud infrastructure (AWS, Azure, GCP) without agents. Its AI graph correlates risks to show you "toxic combinations"—like a database that is both unencrypted and accessible to the public internet.10. Recorded FutureCategory: Threat IntelligenceThis tool scrapes the dark web, forums, and code repositories using natural language processing to predict attacks before they happen, giving your team a heads-up on emerging campaigns targeting your industry.

Coding in 2026 isn't about writing syntax; it's about orchestrating intelligence. The developer who ignores AI agents is the new "assembly programmer"—technically skilled, but too slow for modern velocity.After testing dozens of platforms, we have curated the definitive list of the top 10 AI tools that are redefining software engineering this year.1. CursorBest for: The "AI-Native" IDECursor has effectively replaced VS Code for serious AI-assisted development. Unlike plugins that just autocomplete, Cursor indexes your entire codebase. You can highlight code and ask, "Refactor this legacy function to use async/await and add error handling," and it executes the changes directly in the editor.2. GitHub Copilot WorkspaceBest for: Issue-to-PR AutomationCopilot has evolved from a chat bot to a full agent. With Workspace, you can open a GitHub Issue, and the AI plans the solution, edits multiple files across the repository, and fixes build errors before you even review the Pull Request.3. Devin (by Cognition)Best for: Autonomous EngineeringDevin is the world’s first fully autonomous AI software engineer. It doesn't just write code; it has its own command line, browser, and editor. It can read documentation, learn new frameworks, and deploy apps end-to-end while you focus on architecture.4. Codeium EnterpriseBest for: Self-Hosted/Air-Gapped TeamsFor enterprises that cannot send IP to the public cloud, Codeium offers the industry-leading self-hosted solution. It provides state-of-the-art autocomplete and chat capabilities that run entirely within your firewall.5. WarpBest for: Command Line ProductivityWarp reinvents the terminal for the AI age. Instead of memorizing complex `tar` or `ffmpeg` flags, you simply type natural language (e.g., "undo the last git commit but keep the changes staged"), and Warp generates and executes the correct shell command.6. MintlifyBest for: Documentation on AutopilotEngineers hate writing docs. Mintlify scans your code and generates beautiful, user-friendly documentation websites automatically. Crucially, it monitors your PRs and updates the docs whenever code logic changes, ensuring nothing goes stale.7. Snyk DeepCode AIBest for: Security ScanningSnyk uses AI to spot vulnerabilities in real-time. It goes beyond simple linting by understanding the flow of data through your application, catching complex issues like SQL injections or hardcoded secrets before they reach production.8. Postman AIBest for: API Testing & DocumentationPostman’s AI features can automatically generate test suites for your endpoints, visualize API responses, and write documentation, saving countless hours of manual QA work.9. Perplexity (Developer Mode)Best for: Technical SearchStackOverflow traffic is down for a reason. Perplexity scans the latest documentation and library updates to answer technical questions instantly, citing sources so you can verify the code is up to date for 2026 standards.10. TabnineBest for: Personalized Code CompletionWhile other tools are generic, Tabnine excels at learning *your* team's specific coding style and best practices. The more you use it, the more it mimics your variable naming conventions and architectural patterns.

In 2026, the barrier between a creative idea and a finished animation has virtually vanished. AI video engines have evolved to handle complex physics, consistent character design, and cinematic lighting in seconds.If you're looking for professional-grade results without a heavy subscription, here are the top 5 free (or "freemium") AI animation generators leading the market today.1. CapCutBest for: All-in-One Social Media Animation CapCut has evolved from a simple mobile editor into a dominant AI video suite. Its Text-to-Video engine is one of the most generous in the industry, offering high-quality AI generation for free with seamless integration into its legendary editing timeline.Key Features: AI Dialogue Scenes for synchronized lip-syncing and a massive library of AI-powered templates.Why it's fast: You can generate a clip and instantly apply transitions, captions, and effects in the same app.Free Status: Generous free tier with high-resolution exports and no watermarks on many features.2. Kling AIBest for: Realistic Motion & Physical Accuracy Kling has taken the internet by storm in 2026 for its ability to generate ultra-realistic human movements and complex interactions that other models struggle with (like eating or fluid hair motion).Key Features: Generates clips up to 10 seconds with incredible spatial consistency and 1080p resolution.Why it's high quality: Its "U-ViT" architecture ensures that characters don't "morph" or lose their shape during movement.Free Status: Offers a daily refill of 66 free credits, allowing for roughly 6 free videos every single day.3. Luma Dream MachineBest for: Cinematic Lighting & Artistic Style Luma’s Dream Machine (now in its Ray3 iteration) is the go-to for creators who want their animations to look like big-budget films. It excels at atmospheric lighting and "epic" camera movements.Key Features: Excellent Image-to-Video capabilities—simply upload a character sketch and Luma breathes life into it.Why it's fast: The rendering engine is optimized for speed, often delivering a 5-second cinematic clip in under 120 seconds.Free Status: Includes a free tier with 30 monthly generations (refills monthly).4. Invideo AIBest for: Script-to-Animation Automation If you have a script but no visual assets, Invideo is your "AI Co-pilot." It acts as a full production house, automatically selecting stock footage, generating AI clips, and adding voiceovers based on your prompt.Key Features: A "Video Co-pilot" that allows you to edit the video using chat commands (e.g., "Make the second scene more dramatic").Why it's fast: It handles the storytelling, editing, and voiceover in one single workflow.Free Status: Provides 10 minutes of AI video generation per week (with a watermark on exports).5. Leonardo.ai (Motion)Best for: Character Consistency & Artistic Control Leonardo.ai is famous for its image generation, but its Motion tool is a powerhouse for animating those images while keeping the character's face and style 100% consistent.Key Features: "Motion Strength" sliders that allow you to control exactly how much movement you want in a scene.Why it's high quality: Perfect for "Storyboard-to-Video" workflows where you need the character to look exactly the same across different scenes.Free Status: Uses a "Token" system; users receive 150 tokens daily, which can be used for both images and video motion.

In 2026, the YouTube feed is more competitive than ever. With thousands of videos uploaded every minute, your thumbnail is the only thing standing between a scroll and a click.Leveraging AI doesn't just save time—it allows you to use data-driven design to "hack" the human brain for higher click-through rates (CTR). Here are 10 essential tips to supercharge your thumbnails using today’s most powerful AI tools.1. Generate Hyper-Realistic Subjects with Midjourney or DALL-E 3Forget generic stock photos. Use AI image generators to create specific, high-quality subjects that perfectly match your video’s theme.The Trick: Use prompts that specify "dramatic lighting" or "ultra-detailed textures" to make the subject pop against a busy feed.2. Swap Faces for Consistent BrandingPersonal branding is key in 2026. Tools like InsightFaceSwap or Remaker AI allow you to place your own face onto any AI-generated character or high-action scene.Benefit: You can look like you’re in the middle of a desert, underwater, or in outer space without ever leaving your desk.3. Use AI Background Removal for "Layered" DesignsClean thumbnails require separation between the subject and the background. Use Adobe Express or Canva’s Magic Eraser to instantly isolate yourself.Pro-Tip: Once the background is removed, add a slight "outer glow" or white stroke around your body to create a 3D effect that stands out.4. Optimize Color Palettes with Predictive AIColors evoke emotion. Use AI tools like VidIQ’s Thumbnail Analyzer to see which colors are currently trending in your specific niche.Strategy: If your competitors all use red, use AI to suggest a high-contrast alternative like neon green or electric blue to break the pattern.5. Create "Action Expressions" with AI RetouchingStudies show that expressive faces (shock, joy, fear) get more clicks. If your original photo is too "flat," use FaceApp or Lensa to subtly enhance facial expressions or widen eyes for a more dramatic look.6. Let AI Check Your "Mobile-First" ReadabilityOver 70% of YouTube views happen on mobile. AI-driven preview tools like ThumbsUp.tv allow you to see how your thumbnail looks at tiny sizes.Focus: If the AI preview shows your text is unreadable, it’s time to simplify.7. Run AI-Powered A/B TestingDon't guess—test. Use Test & Compare (YouTube’s native tool) or ThumbnailTest.com to let AI determine which version of your design actually converts.Goal: Test two vastly different concepts (e.g., one with text vs. one without) to see what your specific audience prefers.8. Remove Distractions with "Generative Fill"If your perfect photo has a messy background or a random object in the frame, use Photoshop’s Generative Fill to erase it.Why it works: A "clean" thumbnail focuses the viewer’s eye exactly where you want it: on the main subject and the title.9. Match the "Emotional Temperature" of the VideoAI sentiment analysis tools can analyze your script and suggest a thumbnail style that matches. If your video is a "Scary Mystery," tools like Leonardo.ai can generate "Dark Cinematic" style backgrounds that set the mood before the viewer even clicks.10. Use AI to Generate Bold, Short Text OverlaysThe best thumbnails have 3 words or less. Use ChatGPT to brainstorm "High-CTR Phrases" based on your video title.Example: Instead of "How to make a pizza," AI might suggest "Secret Pizza Hack!" or "Never Buy Pizza."

1. Otter.aiBest for: Automated Meeting Intelligence Otter is the gold standard for corporate meetings. It doesn't just transcribe; it acts as a virtual assistant that attends your calls even when you can't.Key Features: * OtterPilot: Automatically joins Zoom, Google Meet, and Microsoft Teams.Real-time Summaries: Generates live meeting notes with clickable highlights.Speaker Identification: Accurately labels different voices in a conversation.Best For: Project managers and consultants who need a searchable record of every discussion.2. DescriptBest for: Content Creators & Editors Descript revolutionized the industry by treating audio like a text document. To edit your audio or video, you simply edit the transcript.Key Features:Overdub: Create an AI clone of your voice to "type" in corrections to your audio.Studio Sound: Removes background noise and enhances voice quality with one click.Filler Word Removal: Automatically identifies and deletes "ums" and "uhs."Best For: Podcasters, YouTubers, and social media marketers.3. Dragon ProfessionalBest for: Legal and Medical Accuracy Owned by Nuance (Microsoft), Dragon remains the titan of specialized transcription. It is built for industries where "close enough" isn't good enough.Key Features:Deep Learning: Adapts to your unique accent and environmental acoustics.Custom Vocabularies: Massive libraries for legal, medical, and technical terminology.Hands-Free PC Control: Allows users to control their entire OS via voice.Best For: Lawyers, doctors, and individuals with accessibility needs.4. Fireflies.aiBest for: Sales and CRM Integration Fireflies focuses on the "searchability" of conversations. It is designed to turn voice data into actionable business intelligence.Key Features:Smart Search: Filter by keywords, action items, dates, and metrics.CRM Sync: Automatically pushes meeting notes into Salesforce, HubSpot, or Pipedrive.Sentiment Analysis: Identifies the tone and mood of the speakers.Best For: Sales teams and recruiters tracking candidate or client interactions.5. Rev.aiBest for: High-Fidelity API Solutions Rev is famous for its human transcription, but its AI engine (Rev.ai) is one of the most accurate in the world, powered by millions of hours of human-transcribed data.Key Features:World-Class Accuracy: Consistently outperforms many "Big Tech" speech engines.Global Language Support: High accuracy across 36+ different languages.Topic Extraction: Summarizes the main themes of a recording automatically.Best For: Developers and researchers needing high-accuracy bulk transcription.6. TrintBest for: Journalists and Newsrooms Trint is built for the "storyteller" workflow. It allows teams to collaborate on a single transcript in real-time to find the "perfect quote" for a story.Key Features:Collaborative Editor: Highlight and comment on transcripts with your team.Roughcut Tool: Pull segments from multiple transcripts into a single storyboard.Mobile App: Record and transcribe on the go for field reporting.Best For: News organizations and documentary filmmakers.7. Scribe (by OpenAI)Best for: Minimalist, State-of-the-Art Accuracy Utilizing the Whisper architecture, various tools (like Whisper Memos or Scribe) offer the most advanced noise-canceling transcription available today.Key Features:Multi-Lingual Translation: Can transcribe in one language and translate to another instantly.Punctuation Mastery: Handles long-form dictation with perfect grammar and paragraph breaks.Clean Output: Unlike older tools, it rarely gets "tripped up" by background music or low-quality mics.Best For: Writers and researchers who need a "brain dump" turned into a clean draft.

New data released by Eurostat reveals a significant generational gap in the adoption of artificial intelligence across the European Union. As of 2025, 63.8% of young people aged 16–24 have used generative AI tools—nearly double the adoption rate of the general population (32.7%).Education and Personal Use Driving GrowthWhile AI is becoming a staple in daily life, the motivations for using it vary significantly by age:Education: Unsurprisingly, students are the primary drivers of this trend. Nearly 40% of young people use AI for formal education, compared to less than 10% of the wider population.Private Life: Young people are also more likely to experiment with AI for personal projects or entertainment, with 44.2% reporting private use.Workplace: Interestingly, professional use of AI remains steady across age groups, hovering around 15%. This parity is largely because many in the 16–24 demographic are students who have not yet entered the full-time labor market.Regional Highlights: Where AI is Most PopularThe adoption of generative AI is not uniform across the EU. The tech is most prevalent in Northern and Southern Europe:Top Adopters: Greece leads the EU with 83.5% of its youth using AI, followed closely by Estonia (82.8%) and Czechia (78.5%).Lowest Adoption: On the other end of the spectrum, youth in Romania (44.1%), Italy (47.2%), and Poland (49.3%) reported the lowest usage rates, though even these figures show significant engagement.About the DataGenerative AI refers to tools that can create new text, images, or code based on user prompts. These findings are part of the 2025 EU survey on ICT usage in households, reflecting digital experiences over a three-month period. The release of this data highlights the evolving digital landscape as the EU marks Safer Internet Day 2026, emphasizing the importance of digital literacy for the next generation.

OpenAI’s highly anticipated foray into hardware is coming into clearer focus, though fans will have to wait a bit longer than originally expected. The company’s first AI-powered device is now slated for a 2027 release, and it will debut without the "io" branding that was initially associated with the project.Key Details of the Upcoming Launch:Release Timeline: While early rumors suggested a 2026 debut, updated reports indicate that mass production is now targeted for 2027.Branding Shift: The device will no longer use the "io" brand name. This change follows a legal dispute with a Google Ventures-backed startup called iyO, which claimed the name was too similar to its own.The Design Team: Despite the name change, the project remains a collaboration between OpenAI CEO Sam Altman and legendary former Apple designer Jony Ive. The hardware division is currently led by OpenAI executive Peter Welinder.Hardware Concept: * Screenless Design: The gadget is expected to be a "screenless" device, relying entirely on voice interaction and environmental sensing.Form Factor: Early prototypes are described as compact and minimalist—roughly the size of an iPod Shuffle.Sensors: It will feature high-end cameras and microphones to "see" and "hear" the user’s surroundings, allowing the AI to provide context-aware assistance.Strategic Production: To avoid geopolitical complications and supply chain risks, OpenAI is reportedly looking at Vietnam as the primary assembly location rather than China.Why It MattersSam Altman has reportedly told employees that this hardware could be "the biggest thing" the company has ever done, with internal goals of selling up to 100 million units. By moving away from the smartphone "screen" model, OpenAI and Ive aim to create a more natural, ambient way to interact with artificial intelligence, potentially positioning the device as a "third primary device" alongside the laptop and the phone.

Nvidia has announced a $2 billion investment in CoreWeave to help the cloud infrastructure company significantly expand its artificial intelligence computing capacity. The move comes as demand for AI compute continues to rise rapidly, driven by the growth of large language models and other data-intensive AI applications.The investment will support CoreWeave’s plan to add more than 5 gigawatts of AI computing power over the coming years. This expansion is expected to include the construction of new large-scale data centers designed specifically for high-performance AI workloads. CoreWeave, which originally started as a cryptocurrency mining company, has pivoted aggressively toward AI infrastructure but has also taken on substantial debt to fund its rapid growth.As part of the deal, Nvidia becomes one of CoreWeave’s largest shareholders, strengthening the strategic partnership between the two companies. CoreWeave relies heavily on Nvidia’s graphics processing units and related technologies, which are widely used for training and running advanced AI models.The partnership will also deepen technical collaboration, with CoreWeave planning to deploy multiple generations of Nvidia hardware across its platform. This is expected to improve efficiency and performance for customers ranging from AI startups to large enterprises.Industry analysts view the investment as a sign of Nvidia’s growing role not just as a chip supplier, but as a key financier and enabler of global AI infrastructure. The deal highlights the intense competition among cloud and technology companies to secure enough computing power to support the next wave of AI innovation.

A group of YouTube creators has filed a lawsuit against Snap Inc., accusing the company of using their copyrighted videos without permission to train artificial intelligence models used in Snapchat features. The case, filed in a U.S. federal court, adds Snap to a growing number of technology companies facing legal challenges over how they source data for AI development.The plaintiffs include several well-known YouTubers with millions of combined subscribers. They allege that Snap relied on large video datasets containing their content to train AI systems, despite the videos being protected by copyright and subject to platform restrictions. According to the complaint, these datasets were originally intended for academic research and not for commercial use.The lawsuit claims that Snap used the trained models to develop and improve generative AI tools within Snapchat, including features that allow users to create or edit images using text prompts. The creators argue that this process involved unauthorized copying and use of their videos, violating U.S. copyright law.The plaintiffs are seeking financial damages as well as a court order to prevent Snap from continuing to use copyrighted content in AI training without proper authorization. They are also pursuing class-action status on behalf of other creators whose videos may have been included in the datasets.The case highlights increasing tension between content creators and tech companies as artificial intelligence becomes more widespread. Legal experts say the outcome could have significant implications for how AI models are trained and how copyrighted material is treated in the future. Snap has not publicly commented on the lawsuit.

Microsoft has announced a major development in its artificial intelligence strategy with the launch of its in-house AI accelerator chip, the Maia 200, just days before releasing its quarterly earnings. This move underscores the company’s push to control more of the technology stack behind its cloud-based AI services and reduce its reliance on external semiconductor suppliers.The Maia 200 is designed specifically for AI inference workloads — the computing tasks needed to run trained machine-learning models — and is built on a state-of-the-art 3-nanometer process. According to Microsoft, the chip delivers significantly improved performance and efficiency compared with previous systems and some competing hardware from other cloud providers, offering up to 30 % better performance per dollar. It contains over 140 billion transistors and supports high-bandwidth memory, enabling faster AI operations at lower operating costs.Microsoft says the Maia 200 is already being deployed in its Azure data center in Iowa, with plans to expand to additional regions. The company also previewed a new software development kit to help developers optimize AI models for the Maia platform.The launch marks a strategic shift for Microsoft as it moves beyond being mainly a customer of third-party chips toward designing custom silicon tailored for its own large-scale AI infrastructure. This comes at a time when major cloud companies, including Amazon and Google, are also developing their own AI chips to compete with traditional GPU vendors.Investors have taken note, with Microsoft’s shares showing resilience ahead of the earnings announcement. As the company prepares to report its financial results, analysts will be watching closely to see how investments in proprietary AI hardware like Maia 200 contribute to growth in its cloud and AI businesses.

Ultra-realistic cinematic Christmas interior scene inspired by the reference image. A clean-shaven man with the exact facial features, face shape, skin tone, and proportions of the uploaded photo is sitting casually on a small wooden ladder while decorating a Christmas tree. He is wearing cozy Christmas-themed pajamas: red and green plaid pants, a dark sweater, and a playful Santa hat slightly tilted on his head. His hair and face remain clearly visible, natural and realistic.He is holding a string of colorful Christmas lights in his hands, looking at them with a slightly amused and focused expression. The lights are partially tangled around him and the ladder, creating a fun, candid moment. A fully decorated Christmas tree stands beside him, filled with ornaments, garlands, and warm glowing lights. At the bottom, a friendly dog wearing a small Santa hat looks up toward him, adding warmth and humor to the scene.The environment is a cozy living room with framed artwork on the wall, warm ambient lighting, and a nostalgic holiday atmosphere. Soft shadows, realistic indoor light balance, natural skin texture (no oily look, no plastic skin), shallow depth of field, cinematic color grading, high-end lifestyle photography style, ultra-detailed realism, Nano Banana quality,8K detail, no text, no logos, no watermarks.Ultra-realistic cinematic night scene inspired by the reference image. A clean-shaven man with the exact facial structure, skin tone, and proportions of the uploaded photo stands behind professional DJ decks, fully immersed in a chaotic Christmas party atmosphere. No beard, no Santa hat, hair visible and naturally styled, confident and focused expression.He wears a modern Christmas-themed outfit: a red velvet jacket with white fur trim (Santa-inspired but contemporary), open collar, no costume exaggeration.The DJ booth is surrounded by glowing neon Christmas lights, colorful reflections, and light snowfall particles in the air.Behind him, a vibrant neon sign reads "MERRY XMAS" in bold glowing letters, with festive neon illustrations around it (Santa face outline, bells, Christmas icons). A crowd of people in the background raises their hands, cheering and dancing, slightly blurred for depth.Cinematic lighting with strong neon reds, greens, and warm highlights, dramatic shadows, volumetric light rays, realistic reflections on DJ equipment, sweat-free natural skin texture (no oily look, no plastic skin). Shallow depth of field, high contrast color grading, ultra-detailed facial realism, premium nightlife photography style, high-end editorial realism, NanoBanana quality, 8K detail.Ultra-realistic cinematic indoor night scene. On the LEFT, a man inspired by the uploaded reference photo sits on a couch wearing a cozy but stylish Christmas sweater, holding a PlayStation controller, focused expression. On the RIGHT, The Grinch is sitting next to him, leaning forward aggressively with a controller, competitive grin on his face. A large TV in front shows a blurred football or racing game. Christmas tree lights softly illuminate the room, pizza boxes and energy drinks on the table. Warm ambient lighting mixed with neon TV glow, realistic skin and fur textures, cinematic depth of field, premium lifestyle realism, 8K quality.Ultra-realistic cinematic Christmas portrait inspired by the reference image, without any text or typography. A clean-shaven man with the same facial features, face shape, skin tone, and proportions as the uploaded photo stands centered in a snowy winter forest at night. He is wearing a classic red Santa-style jacket with white fur trim, white gloves, and a wide belt, no Santa hat. His hair is visible and naturally styled, warm confident smile, friendly but premium expression.He carries a large green sack over his shoulders filled with neatly wrapped Christmas gifts in red, green, and gold wrapping paper, decorated with bows. Soft snowfall surrounds him, snow-covered trees fade into the background with cinematic depth. Cool blue winter tones contrast with the warm reds and greens of the outfit and gifts.Cinematic soft lighting, subtle rim light separating the subject from the background, natural skin texture (no oily look, no plastic skin), sharp facial detail, shallow depth of field, luxury holiday editorial photography style, clean composition, no logos, no text, no watermarks, ultra-detailed, Nano Banana quality, 8K realism.A photorealistic portrait of a man wearing a festive red Christmas sweater with green and gold embroidered patterns. He has a well-groomed full beard and neatly styled hair. The man stands in a relaxed pose with his hands in his pockets, looking slightly off-camera with a calm and confident expression. The background is a smooth, rich red gradient with soft studio lighting creating warm highlights and gentle shadows. The overall atmosphere is modern, cinematic, and cozy, emphasizing holiday colors and clean minimal composition.A dramatic close-up portrait of a man wearing a Santa hat and round vintage sunglasses. He is tearing through a sheet of red paper, pulling the ripped edges open with both hands. The man's expression is serious and intense, with a strong facial features. The background is bright red with subtle snow particles floating in the air. Lighting is soft studio lighting with a slightly moody contrast, highlighting the texture of the torn paper and the Santa hat's fluffy white trim. The image should be highly photorealistic, sharp, and cinematic, with a festive but bold atmosphere.Use the woman from my uploaded image with her face preserved exactly. Place her outdoors during gentle snowfall, illuminated by warm golden Christmas lights.Dress her in a chic winter coat with a white scarf. Add soft snowflakes on her hair and shoulders. Ultra-detailed, dreamy Christmas vibe, magazine-cover quality."Create a glamorous Christmas portrait of the same woman from my uploaded image, keeping her facial features unchanged. Style her in a sparkling red sequin dress with soft golden Christmas bokeh lights behind her. Add a subtle warm glow, holiday makeup, and elegant soft curls. Ultra-realistic, cinematic lighting, festive and modern.Create an ultra-realistic Christmas portrait using the same woman from my uploaded image while keeping her face unchanged. Dress her in a luxurious velvet Santa coat with soft white fur trim. Add a perfectly styled Santa hat, glossy holiday makeup, and glowing warm bokeh lights behind her. Rich colors, cinematic realism, sparkling festive atmosphere, Instagram-viral quality.

Its obvious that ChatGPTs writing can sometimes feel robotic. But with the right prompts, it can sound just like a real person. Through trial and error, I found 10 prompts that helped ChatGPT write in a more natural and engaging way. Let’s checkout these prompts and see how they work.ALSO READ: Claude 3.5 Sonnet Update: Everything You Need To KnowGet my Complete AI BundleUnderstanding ChatGPT’s Strengths and LimitationsFrom my experience, ChatGPT has its pros and cons. Here’s a quick breakdown:Strengths:1. Speed: It generates responses quickly, which is great for brainstorming.2. Flexibility: It can help with everything from articles to coding.3. Clear structure: It provides well-organized answers.Limitations:1. Robotic tone: Sometimes, the responses sound too formal.2. Emotionless: It often misses emotional nuance in writing.3. Loses context: In longer conversations, it can forget earlier details.Despite these limitations, ChatGPT can be incredibly useful when completing assignments.For example, if you’re struggling to wrap up your paper, you can use EssayHub to generate conclusions for papers.This tool can help you craft a conclusion that effectively summarizes your main points, reinforces your thesis, and leaves a strong, lasting impression.Whether you’re writing an essay, research paper, or any other academic task, EssayService can ensure your conclusion is well-crafted and aligned with your overall argument.Why Human-like Writing Is Important for ContentWriting that feels human is essential for connecting with readers. Here’s why:1. Engagement: People are more likely to stay interested when the content feels relatable and conversational.Mastering prompts to make AI writing sound authentically human can transform content creation, especially in keeping audiences captivated.When text feels approachable and chatty, it naturally pulls readers in and maintains their attention.Similarly, an effective ad server in the advertising realm employs this principle by serving ads that blend effortlessly into the user journey, ensuring engagement remains high without any disruptive vibes.2. Trust: Natural writing builds a connection, making the writer seem more trustworthy.3. Clarity: Human-like writing simplifies complex ideas, making them easier to understand.4. Tone: A friendly tone creates a more enjoyable reading experience.5. Connection: It feels like you’re having a conversation, which makes the content more memorable.By guiding ChatGPT with the right prompts, we can make sure the writing hits all these marks.Use a Conversational ToneRecently, I was writing a blog post, and the tone felt too formal and stiff. I wanted it to sound more personal, like a conversation. So, I used this prompt:ChatGPT Prompt:Act as if youre speaking to a close friend about [insert topic here]. Keep the tone friendly, light, and engaging. Use casual phrases like [friendly phrase] (‘Here’s what I think...’) or [conversational phrase] (‘You won’t believe this, but...’). Make sure the sentences are short and flow naturally, with relaxed connectors like [connector] (‘So,’ ‘Well,’). Add a few casual questions like [question] (‘What do you think?’ or ‘Can you imagine that?’) to keep the conversation interactive. Don’t be afraid to use informal words to make the reader feel comfortable.ChatGPT Response:Use a Conversational ToneUse a Conversational ToneFrom the response you will notice the relaxed phrases and casual vibe make it feel like you’re just chatting with a friend, which makes the message easier to connect with.Add Personal Stories or ExperiencesChatGPT Prompt:Act as if youre sharing a personal experience to illustrate [insert topic here]. Use relatable phrases like [personal phrase] (‘I once had an experience where...’) or [shared moment] (‘This reminds me of a time when...’). Ensure the story connects directly to the topic, using examples like [specific example] (‘This happened when...’ or ‘I felt the same way when...’). Keep the tone friendly and engaging, so the reader feels like they’re getting real-life insights from you.ChatGPT Response:Add Personal Stories or ExperiencesAdd Personal Stories or ExperiencesNotice how sharing stories makes the response feel real and relatable, like you’re hearing someone’s genuine experience instead of being lectured.Focus on Specific EmotionsChatGPT Prompt:Act as if youre trying to evoke [insert emotion here] in the reader. Use emotional language such as [emotion phrase] (‘It made me feel...’) or [empathy statement] (‘Can you imagine how it feels to...?’). Make sure every part of the text emphasizes this emotion, adding phrases like [emotion-driven description] (‘It was overwhelming...’ or ‘It filled me with joy when...’). The goal is to create an emotional connection that makes the reader feel deeply involved.ChatGPT Response:Focus on Specific EmotionsFocus on Specific EmotionsWhen you tap into emotions, it pulls people in.It’s like feeling hope yourself instead of just reading about it."Include Questions in ResponsesChatGPT Prompt:Act as if youre having a conversation about [insert topic here]. Use questions like [open-ended question] (‘Have you ever thought about...?’) or [reflective question] (‘What would you do if...?’). Make sure the questions encourage the reader to think and engage with the content. Sprinkle in interactive elements, such as [engaging question] (‘How do you feel about that?’), to keep the reader reflecting on the topic throughout.ChatGPT Response:Include Questions in ResponsesInclude Questions in ResponsesAsking questions encourages reflection, turning it into a two-way conversation.It makes you think, rather than just passively reading.Write with Shorter, Simple SentencesChatGPT Prompt:Act as if youre explaining [insert topic here] in the simplest way possible. Use short, clear sentences to make the content easy to follow. Include connectors like [simple connector] (‘Next,’ ‘Then,’) and [transitional phrase] (‘After that,’ ‘Finally,’) to guide the flow. Break down complex ideas into bite-sized chunks, ensuring that each sentence is direct and straightforward to help the reader grasp the message quickly.ChatGPT Response:Write with Shorter, Simple SentencesWrite with Shorter, Simple SentencesBreaking things down into small, easy chunks mirrors how people naturally explain things in person—short, simple, and to the point.Add Humor or LightheartednessChatGPT Prompt:Act as if youre trying to make the reader smile while talking about [insert topic here]. Add lighthearted jokes or playful remarks like [humor phrase] (‘Let’s be real...’) or [funny comparison] (‘It’s like trying to juggle water...’). Make sure the humor fits the context and doesn’t overshadow the main message, using relaxed and casual language to keep the tone fun and engaging. Balance the humor with helpful information, so the reader enjoys the content without losing the key point.ChatGPT Response:Add Humor or LightheartednessAdd Humor or LightheartednessThrowing in a joke or playful remark lightens the mood, making it feel fun, like banter with a friend, not just information.Use Everyday Examples and AnalogiesChatGPT Prompt:Act as if youre explaining [insert topic here] using simple, everyday examples. Use phrases like [analogy phrase] (‘It’s like when...’) or [example phrase] (‘Think of it like...’). Make sure the examples are easy to relate to and connected directly to the topic. Add analogies such as [comparison phrase] (‘It’s kind of like when...’) to make the information easier to understand. The goal is to simplify complex ideas by comparing them to things people experience in their daily lives.ChatGPT Response:Use Everyday Examples and AnalogiesUse Everyday Examples and AnalogiesUsing familiar comparisons makes the concept click faster—it’s easier to understand new things when they’re linked to everyday experiences.Be Direct, Not FormalChatGPT Prompt:Act as if youre giving straightforward advice on [insert topic here]. Use direct language like [simple statement] (‘Here’s what matters...’) or [no-nonsense phrase] (‘Let’s cut to the chase...’). Avoid formal language and keep the tone simple and accessible. Include clear instructions or insights like [directive statement] (‘This is what you should do...’). Make sure the writing feels direct and easy to follow, without unnecessary jargon or complexity.ChatGPT Response:Be Direct, Not FormalBe Direct, Not FormalSkipping the fluff and going straight to useful advice feels refreshing, like talking to someone who knows what matters and gets it.Use Casual ConnectorsChatGPT Prompt:Act as if youre having a casual chat about [insert topic here]. Use informal connectors like [connector phrase] (‘So,’ ‘Anyway,’) to keep the flow natural. Include transitions like [casual transition] (‘By the way,’ ‘Oh, and...’) to make the conversation feel smooth and easy. Avoid stiff transitions, focusing on making the writing sound like a relaxed conversation with a friend. Keep the content connected and flowing naturally from one idea to the next.ChatGPT Response:Use Casual ConnectorsUse Casual ConnectorsInformal connectors like ‘By the way’ or ‘Anyway’ mimic real conversations, making the flow feel natural and easygoing.End with a Call to Action or Thought-Provoking QuestionChatGPT Prompt:Act as if youre wrapping up a conversation about [insert topic here] and want the reader to take action or think deeply. End with a strong call to action like [action phrase] (‘What’s your next step?’ or ‘Try it out today.’) or a reflective question like [thought-provoking question] (‘What do you think?’ or ‘How would you handle this?’). Ensure the ending leaves the reader feeling engaged and motivated to either take action or continue thinking about the topic.ChatGPT Response:End with a Call to Action or Thought-Provoking QuestionEnd with a Call to Action or Thought-Provoking QuestionEnding with a reflective question or call to action leaves the conversation open-ended, giving space for deeper thought or immediate action.How to Use These PromptsUsing these prompts effectively will help you get the most out of ChatGPT’s abilities. Here’s how to approach it:1. Be Clear About Your Goal: Start by understanding what you want ChatGPT to achieve. Whether it’s a conversational tone, humor, or adding emotional depth, decide the outcome before you input the prompt.2. Customize the Placeholders: Each prompt includes placeholders like [insert topic here] and [emotional phrase]. Replace these with specific details related to your content.The more specific you are, the more tailored the response will be.3. Experiment with Variations: Don’t hesitate to tweak the prompts to suit your needs. Try different word choices, sentence structures, or tones to see what works best for your particular project.4. Review and Refine the Output: After ChatGPT generates a response, review it carefully. You may need to make minor adjustments to ensure it sounds just the way you want. The initial output is a starting point that you can refine.5. Combine Multiple Prompts: Sometimes, using a combination of these prompts works best. For instance, you could start with a conversational tone and then add humor or emotion to deepen the connection with your audience. Mix and match to get the perfect result.By following these steps, you can craft responses that sound more natural, engaging, and human-like.Wrapping Up: 10 Prompts That Makes Chatgpt Write like a HumanThese prompts are designed to help you get the best response from ChatGPT’s and make its responses sound more like human writing. With a little practice and customization, you’ll be able to create engaging content that resonates with your audience and achieves your goals. Keep experimenting, refining, and adjusting to find the perfect blend for your needs!

Google has made its most powerful AI video creator, Veo 3, available for everyone to use on its Vertex AI platform. And for those who need to work quickly, a speedier version called Veo 3 Fast is also ready-to-go for quick creative work.Ever had a brilliant idea for a video but found yourself held back by the cost, time, or technical skills needed to create it? This tool aims to offer a faster way to turn your text ideas into everything from short films to product demos.70 million videos have been created since May, showing a huge global appetite for these AI video creation tools. Businesses are diving in as well, generating over 6 million videos since they got early access in June.The real-world applications for Veo 3So, what does this look like in the real world? From global design platforms to major advertising agencies, companies are already putting Veo 3 to work. Take design platform Canva, they are building Veo directly into their software to make video creation simple for their users.Cameron Adams, Co-Founder and Chief Product Officer at Canva, said: “Enabling anyone to bring their ideas to life – especially their most creative ones – has been core to Canva’s mission ever since we set out to empower the world to design.“By democratising access to a powerful technology like Google’s Veo 3 inside Canva AI, your big ideas can now be brought to life in the highest quality video and sound, all from within your existing Canva subscription. In true Canva fashion, we’ve built this with an intuitive interface and simple editing tools in place, all backed by Canva Shield.”For creative agencies like BarkleyOKRP, the big wins are speed and quality. They claim to have been so impressed with the latest version that they went back and remade videos.Julie Ray Barr, Senior Vice President Client Experience at BarkleyOKRP, commented: “The rapid advancements from Veo 2 to Veo 3 within such a short time frame on this project have been nothing short of remarkable.“Our team undertook the task of re-creating numerous music videos initially produced with Veo 2 once Veo 3 was released, primarily due to the significantly improved synchronization between voice and mouth movements. The continuous daily progress we are witnessing is truly extraordinary.”It’s even changing how global companies connect with local customers. The investing platform eToro used Veo 3 to create 15 different, fully AI-generated versions of a single advertisement, each customised to a specific country with its own native language.Shay Chikotay, Head of Creative & Content at eToro, said: “With Veo 3, we produced 15 fully AI‑generated versions of our ad, each in the native language of its market, all while capturing real emotion at scale.“Ironically, AI didn’t reduce humanity; it amplified it. Veo 3 lets us tell more stories, in more tongues, with more impact.”Google gives creators a powerful AI video creation toolVeo 3 and Veo 3 Fast are packed with features designed to give you the control to tell complete stories.Create scenes with sound. The AI generates video and audio at the same time, so you can have characters that speak with accurate lip-syncing and sound effects that fit the scene.High quality results. The models produce video in high-definition (1080p), making it good enough for professional marketing campaigns and demos.Reach a global audience easily. Veo 3’s ability to generate dialogue natively makes it much simpler to produce a video once and then translate the dialogue for many different languages.Bring still images to life. A new feature, coming in August, will let you take a single photo, add a text prompt, and watch as Veo animates it into an 8-second video clip.

A new paper from a Samsung AI researcher explains how a small network can beat massive Large Language Models (LLMs) in complex reasoning.In the race for AI supremacy, the industry mantra has often been “bigger is better.” Tech giants have poured billions into creating ever-larger models, but according to Alexia Jolicoeur-Martineau of Samsung SAIL Montréal, a radically different and more efficient path forward is possible with the Tiny Recursive Model (TRM).Using a model with just 7 million parameters, less than 0.01% of the size of leading LLMs, TRM achieves new state-of-the-art results on notoriously difficult benchmarks like the ARC-AGI intelligence test. Samsung’s work challenges the prevailing assumption that sheer scale is the only way to advance the capabilities of AI models, offering a more sustainable and parameter-efficient alternative.Overcoming the limits of scaleWhile LLMs have shown incredible prowess in generating human-like text, their ability to perform complex, multi-step reasoning can be brittle. Because they generate answers token-by-token, a single mistake early in the process can derail the entire solution, leading to an invalid final answer.Techniques like Chain-of-Thought, where a model “thinks out loud” to break down a problem, have been developed to mitigate this. However, these methods are computationally expensive, often require vast amounts of high-quality reasoning data that may not be available, and can still produce flawed logic. Even with these augmentations, LLMs struggle with certain puzzles where perfect logical execution is necessary.Samsung’s work builds upon a recent AI model known as the Hierarchical Reasoning Model (HRM). HRM introduced a novel method using two small neural networks that recursively work on a problem at different frequencies to refine an answer. It showed great promise but was complicated, relying on uncertain biological arguments and complex fixed-point theorems that were not guaranteed to apply.Instead of HRM’s two networks, TRM uses a single, tiny network that recursively improves both its internal “reasoning” and its proposed “answer”.The model is given the question, an initial guess at the answer, and a latent reasoning feature. It first cycles through several steps to refine its latent reasoning based on all three inputs. Then, using this improved reasoning, it updates its prediction for the final answer. This entire process can be repeated up to 16 times, allowing the model to progressively correct its own mistakes in a highly parameter-efficient manner.Counterintuitively, the research discovered that a tiny network with only two layers achieved far better generalisation than a four-layer version. This reduction in size appears to prevent the model from overfitting; a common problem when training on smaller, specialised datasets.TRM also dispenses with the complex mathematical justifications used by its predecessor. The original HRM model required the assumption that its functions converged to a fixed point to justify its training method. TRM bypasses this entirely by simply back-propagating through its full recursion process. This change alone provided a massive boost in performance, improving accuracy on the Sudoku-Extreme benchmark from 56.5% to 87.4% in an ablation study.Samsung’s model smashes AI benchmarks with fewer resourcesThe results speak for themselves. On the Sudoku-Extreme dataset, which uses only 1,000 training examples, TRM achieves an 87.4% test accuracy, a huge leap from HRM’s 55%. On Maze-Hard, a task involving finding long paths through 30×30 mazes, TRM scores 85.3% compared to HRM’s 74.5%.Most notably, TRM makes huge strides on the Abstraction and Reasoning Corpus (ARC-AGI), a benchmark designed to measure true fluid intelligence in AI. With just 7M parameters, TRM achieves 44.6% accuracy on ARC-AGI-1 and 7.8% on ARC-AGI-2. This outperforms HRM, which used a 27M parameter model, and even surpasses many of the world’s largest LLMs. For comparison, Gemini 2.5 Pro scores only 4.9% on ARC-AGI-2.The training process for TRM has also been made more efficient. An adaptive mechanism called ACT – which decides when the model has improved an answer enough and can move to a new data sample – was simplified to remove the need for a second, costly forward pass through the network during each training step. This change was made with no major difference in final generalisation.This research from Samsung presents a compelling argument against the current trajectory of ever-expanding AI models. It shows that by designing architectures that can iteratively reason and self-correct, it is possible to solve extremely difficult problems with a tiny fraction of the computational resources.See also: Google’s new AI agent rewrites code to automate vulnerability fixesBanner for AI & Big Data Expo by TechEx events.Want to learn more about AI and big data from industry leaders? Check out AI & Big Data Expo taking place in Amsterdam, California, and London. The comprehensive event is part of TechEx and is co-located with other leading technology events including the Cyber Security Expo, click here for more information.AI News is powered by TechForge Media. Explore other upcoming enterprise technology events and webinars here.