Google LLC is a global technology company and subsidiary of Alphabet Inc., best known for its search engine, digital advertising business, and a broad ecosystem of consumer and enterprise products. The company develops internet services, cloud infrastructure, mobile and desktop operating systems, and hardware devices used by billions of users worldwide.
This is like giving every shopper their own smart personal assistant that knows the entire store, all the promotions, and the shopperâs preferences, and can guide them from âI have a needâ to âorder placedâ through natural conversation across web, app, or even voice.
This is like putting a smart security camera on all your insurance transactions. It watches events in real time, spots suspicious patterns that look like fraud, and alerts your team before money goes out the door.
This is like an ultra-detailed 3D CAD tool for molecules, powered by AI. Instead of engineers designing car parts, RosettaFold3 designs and predicts how proteins, DNA, and smallâmolecule drugs fit and move together inside the body.
Think of NVIDIA BioNeMo as a set of very smart chemistry and biology "co-pilots" that can read and write molecules and proteins the way ChatGPT reads and writes text. Instead of scientists manually trying out millions of possibilities in the lab, BioNeMo helps them design and screen promising drug candidates on a computer first, massively narrowing the search space.
This is like giving an insurer a living, zoomable map of how cars and drivers behave in the real world, updated in near real time, and then using AI to spot risks, opportunities, and patterns that humans would never see by looking at tables and static reports.
This is like having a smart assistant watch all your videos and automatically create a searchable index of whatâs said, who appears, where logos show up, and key momentsâso teams can quickly find and reuse the right clips without manually scrubbing through footage.
Imagine a huge classroom where different versions of Googleâs Gemini sit sideâbyâside answering the same homework and exam questions. A panel of judges then scores which Gemini answers are most helpful for students. This paper is about building that classroom arena and seeing how good Gemini really is as a learning assistant.
Think of this as building your own âNetflix-styleâ recommendation brain: it watches what each user does, learns their tastes, and then uses a mix of traditional recommendation models and modern generative AI to decide what to show or suggest next.
This is like a superâsmart search and monitoring engine for banks and financial firms that can instantly scan all their data (transactions, logs, customer activity, documents) to spot risks, fraud, and opportunities, then plug into AI tools for answers and automation.
This is like upgrading an insurerâs old spreadsheet-based risk calculator to a smart assistant that not only predicts which policies are risky more accurately, but also clearly explains which customer or policy features drove each prediction.
This is like hiring millions of super-fast digital editors who watch everything posted on a social network in real timeâhiding abusive or illegal content, flagging ruleâbreaking posts, and deciding what to show in peopleâs feeds based on their interests.
Think of the future transport system as a giant, city-wide brain. Instead of each car, bus, or train acting on its own, AI watches traffic, weather, demand, and incidents in real time and then orchestrates everythingâroutes, signals, pricing, and even maintenanceâso people and goods move faster, safer, and cheaper.
This is like having an always-on creative studio that can instantly draft ad copy, images, videos, and campaign ideas on demand, then refine them based on performance data.
This describes how modern social platforms use AI as an alwaysâon assistant that decides what each person sees, when they see it, and how brands can talk to themâso every userâs feed and every ad feel customâmade.
This is like putting GPS trackers on every marketing touchpoint (ads, emails, events) so you can finally see which ones actually helped move a customer from first click all the way to revenue, not just who happened to be last in line.
Think of AI in marketing as a team of tireless digital interns that watch every interaction your customers have with your brand and then help your marketers decide: who to talk to, what to say, when to say it, and on which channelâautomatically and at massive scale.
This is a forward-looking overview of how AI will change digital marketingâlike a roadmap showing how smart tools will increasingly help marketers target the right people, create content, run ads, and measure results with far less manual work.
This is about using AI as a super-smart control center for factories and supply chains. It watches machines, inventory, orders, and logistics in real time, then predicts problems before they happen and suggests the best way to run production so you waste less time, material, and money.
This is like giving your marketing team a super-smart assistant that constantly studies which people click and buy, then automatically adjusts who sees your ads so youâre not wasting money showing ads to the wrong audience.
Imagine a smart assistant that reads millions of toy reviews, call-center notes, and survey comments in minutes, then tells Mattel product teams in plain English what kids and parents love, hate, or are confused by â as those opinions are coming in â so they can quickly tweak designs, instructions, or packaging.
Think of Orbitae AI as a smart control tower for an automotive companyâs data. It connects to all your scattered data sources (production, sales, afterâsales, supply chain), lets managers ask questions in natural language, and then turns complex analytics into simple dashboards, forecasts, and recommendations to run the business better and faster.
This is like putting an extremely fast, tireless safety inspector on every camera around your construction site. It watches video in real time and automatically spots things like workers without helmets, people entering danger zones, or unsafe equipment situations so supervisors can react immediately.
Imagine a super-scientist that can read research papers, look at chemical structures, examine lab images, and understand patient data all at once, then suggest which molecules to try next or which trial designs are most promising. Thatâs what multimodal AI is aiming to do for drug R&D.
Think of this as a guide to how modern AI can act like a very fast, tireless financial analyst: reading huge volumes of data, spotting patterns in markets or risk, and then suggesting what to do next.
This is like a super-smart TV ad matcher that watches the show in real time, figures out what itâs about and who is likely watching, and then picks the most relevant ad to show that viewer â without needing their name or cookies.
Think of todayâs big AI models as brilliant general doctors who know a little about everything but arenât yet safe or precise enough to treat complex, highârisk patients. This paper is about how to retrain and constrain those general doctors so they can safely become topâtier specialists in specific medical tasks, like reading scans, summarizing patient records, or supporting treatment decisions.
This is like having a very fast junior developer who writes code for you, but this guide teaches you how to doubleâcheck that juniorâs work so itâs safe, correct, and secure before it goes into your product.
Think of this as putting a smart assistant behind every part of a trip: it helps people discover where to go, picks good flights and hotels for their budget, updates prices in real time, and steps in when something goes wrong (like delays or overbooking). It learns from thousands of past trips so each new traveler gets a smoother, more personalized journey.
Think of this as upgrading from a dumb FAQ bot to a smart service rep that can actually understand what customers mean, look up the right information, and respond in full sentences across channelsâwithout needing a human every time.
Imagine your whole supply chainâfactories, warehouses, trucks, and suppliersârunning like a smart GPS for your business. It constantly checks traffic (demand), fuel (inventory), and roadblocks (disruptions) and then suggests the best route and timing so you deliver on time with less waste and lower cost.
Think of your companyâs security center as an airport control tower. Traditional tools watch planes (devices, users, emails). This use of AI threat hunting in Defender XDR adds new radar that also watches the AI copilots and automations youâve deployedâso if someone hijacks your AI assistant or uses it to sneak in malware, security can see and stop it.
This is like giving your company a superâlistener that reads what customers write (emails, chats, reviews, social posts) and instantly tells you if theyâre happy, angry, or confusedâat large scale and in real time.
Think of your companyâs network as a city. AI gives both the police and the criminals super-powered binoculars and autopilot cars. Defenders use AI to spot unusual behavior and block attacks faster than humans can. Hackers use AI to scan for weak doors, write convincing scam messages, and automate breakâins at scale.
This is like a smart weather-and-power crystal ball: it looks at recent weather and production data and uses machine learning to predict how much solar and wind power will be generated in the next few hours.
This is about the next generation of digital ad buying, where software agents act like tireless junior media buyers. Instead of humans manually tweaking bids, budgets, and targeting rules in programmatic platforms, AI agents continuously watch performance and automatically adjust campaigns to hit goals like ROAS or CPA.
Imagine your streaming app as a smart host at a party who learns what each guest likes, suggests the right music and games at the right moment, and nudges people before they leave so they stay longer and have more fun. This system uses AI to do that automatically for every user in your mobile entertainment app.
This is like a smart template wizard for documents: you tell it what kind of document you need and some details, and an AI writes a first draft for you that you can then review and edit.
This is like having a smart digital sales associate that quietly watches how people browse, search, and compare products across apps and websites, then helps brands put the right message or product in front of the right shopper at the right time as they move from âjust lookingâ to âIâm ready to buy.â
Think of this as a global field guide to âAI-as-a-junior-lawyerâ: it surveys how tools like ChatGPT-style assistants, contract analyzers, and legal research bots are being used in law firms and inâhouse teams around the world, and what that means for cost, risk, and competitiveness.
Think of this as turning todayâs security analysts into âAI-augmented guardiansâ: people who use smart tools that can spot cyberattacks much faster than humans, while also learning how to control and question those tools so they donât make dangerous mistakes.
Like a 24/7 digital front-desk clerk that can answer questions and help guests book hotel rooms automatically over chat or web.
This is like giving every student their own smart tutor that learns how they learn, adjusts lessons and exercises to their pace, and gives teachers a dashboard to see who needs what helpâautomatically.
This is like giving every hotel guest their own 24/7 digital concierge on their phone. Guests can message a smart assistant to ask questions, request services, or get recommendationsâwithout calling the front desk.
Think of this as a smart co-pilot for programmers: it reads what youâre writing and the surrounding code, then suggests code, tests, and fixesâsimilar to autocorrect and autocomplete, but for entire software features.
This is like having a super-smart app developer sitting next to you while you describe what you want in plain English. You say the âvibeâ of the app â who itâs for, what it should roughly do â and the AI fills in the technical details, wiring screens, data and logic so a working app appears much faster than with traditional coding.
This is like giving every software developer a smart co-pilot that suggests code as they type, understands your codebase, and can help write, refactor, or explain codeâwhile staying under your companyâs control instead of sending everything to a public cloud AI.
Think of modern AI in schools as a super-smart homework helper and writing coach that students can use at any time. It can draft essays, solve math problems, and explain concepts in plain languageâsometimes so well that itâs hard to tell what work is the studentâs and what work is the AIâs.
Think of this as a team of always-on smart assistants for an insurance company: one that drafts and reviews policies, one that answers customer questions, one that reads long claim files and medical reports, and one that helps underwriters and actuaries make sense of mountains of data.
Think of this as a super-smart teaching assistant that can instantly create practice questions, explain hard concepts in simpler words, draft lesson plans, and give students personalized feedback 24/7.
Think of Amazon Q Developer as a smart engineering sidekick that lives inside your AWS and dev tools. You describe what you want in plain English, and it helps you write, debug, and modernize code, understand cloud architectures, and work with AWS services much faster.
This is about using smart software that learns from patterns in network traffic and user behavior to spot hackers and suspicious activity much faster than human teams or rule-based tools can, and then automatically block or contain threats before they spread.
Think of this as a super-fast, tireless junior claims adjuster. It reads claim documents, pulls out all the important details, checks rules, and drafts decisions or next steps so your human team only needs to review the tricky edge cases.
Think of this as building âco-pilotâ assistants for programmers that can read and write code, help with designs, find bugs, and keep big software projects on trackâlike giving every developer a smart, tireless junior engineer who has read all your code and documentation.
This is about tools like GitHub Copilot or ChatGPT that sit inside a developerâs editor and suggest code as they typeâlike an auto-complete on steroids for programmers. The articleâs core claim is that, in real-world use, these assistants donât actually save as much time as the hype suggests.
This is like having a digital ad agency in a box: you type what you want to promote, and the AI helps you generate ad creatives, copy, and campaigns in minutes across channels.
This is a guide showing how to plug âAI helpersâ into every step of your software development process so your developers have smart assistants that can plan, write, review, and maintain code alongside them.
This is like giving the electric grid a very smart traffic controller that can predict and reroute power flows in real time so lights stay on and renewable energy is used more efficiently.
Think of GitHub Copilot as an AI pairâprogrammer that sits in your code editor and guesses what you want to type next, suggesting whole lines or functions based on what youâve already written and your comments.
Imagine every time you open your TV, thereâs a smart concierge who has watched everything youâve ever seen, remembers what you liked, what you quit after 5 minutes, what you binged in a weekend, and what people like you enjoy. That concierge quietly rearranges the shelves so the things youâre most likely to love are always right in front of you. Thatâs what a Netflix-style recommender system doesâat software scale for millions of viewers.
Think of AI in games as a super-fast assistant concept artist or junior designer: it can draft levels, story ideas, or graphics in seconds, but it still needs a human game designer to decide whatâs fun, meaningful, and on-brand.
Think of SGuard-v1 as a smart safety filter that sits in front of your AI systems used in mining operations. Whenever staff or contractors ask the AI something risky (for example about unsafe procedures, explosives, or bypassing regulations), SGuard-v1 checks the request and the AIâs response, and blocks, rewrites, or flags anything that could cause harm or violate safety and compliance rules.
Like giving every online shopper their own smart in-store salesperson who knows the catalog, can answer questions, suggest outfits, and guide them to the right products in real time.
Think of AIOps platforms as a 24/7 AI control tower for your IT systems. They watch logs, metrics, and alerts from all your tools, spot patterns humans would miss, and automatically fix or route problems before they become outages.
This is like giving every college student a 24/7 smart study coach that can explain concepts in simple terms, quiz them, and help them plan their learning, rather than just giving them another digital textbook.
Think of this as a super-watchful digital guardian angel for banks. It constantly looks at payments, credit decisions and customer behavior to spot anything risky or suspicious in real time â much faster and more accurately than human teams alone.
This is like hiring a 24/7 digital concierge and receptionist that chats with your guests on your website, apps, or messaging channels, answering questions, taking bookings, and handling common requests automatically.
Imagine every shopper having a smart helper that knows sales, products, and your preferences, and can do the comparing, searching, and asking-customer-service-questions for you before you ever talk to a human or visit a store.
This is like an intelligent flight simulator for radiologists in training: instead of just reading textbooks, learners practice on realistic imaging cases while an AI tutor adapts to their level, points out what they missed on the scans, and helps them learn faster and more safely before treating real patients.
This is like giving your security team an AI co-pilot that watches everything in your environment in real time, spots attacker behavior (including AI-generated attacks) faster than humans can, and automatically helps block and contain those attacks before they spread.
This is like giving your online store a smarter salesperson who understands spoken questions (voice search) and photos (visual search), then guides shoppers to exactly what they want so theyâre more likely to buy.
This is like putting a smart security guard in your cloud data center who never sleeps, learns what ânormalâ looks like, and automatically flags or blocks suspicious behavior before it turns into a breach.
This is like an AI pair-programmer built directly into Visual Studio Code. As you type, it suggests whole lines or blocks of code, helps write tests, explains code, and can transform comments or natural language into working code snippets.
This is like giving your developers a smart co-pilot inside JetBrains IDEs that can read and write code, explain it, and help with everyday tasks without leaving their usual tools.
Think of this as a super-smart lab assistant for battery scientists: it looks at huge amounts of test data from lithium-ion batteries and then suggests the best recipes and operating conditions to make batteries last longer, charge faster, and be saferâwithout having to run every experiment physically.
Think of AI code assistants as smart copilots for programmers. As you type, they guess what youâre trying to build and suggest code, explain errors, write tests, and help you understand unfamiliar code â like an alwaysâavailable senior engineer sitting next to every developer.
GitHub Copilot is like an AI pair-programmer that sits in your code editor and suggests whole lines or blocks of code as you type, based on your comments and existing code.
This is like giving eDiscovery and litigation support teams a super-smart research assistant that can read huge piles of documents, understand what they say, and answer questions about them in plain Englishâwithout replacing the lawyersâ judgment.
This is a guide about using tools like ChatGPT-style content generators and AI media tools to create marketing content faster so more people discover and visit your brand online.
This is like giving your existing code to a very smart assistant and asking it to write the unit tests for you. The large language model reads the code, guesses what it should do, and then writes test cases to check that behavior automatically.
This is like having a super-smart digital assistant for the sports world that can instantly answer questions, create reports, draft commentary, and analyze information for coaches, teams, media, and fans.
This is the kind of AI that decides âBecause you watched X, youâll probably like Yâ on Netflix, YouTube, or Spotify. It watches what each user does, compares that to millions of other users, and then builds a constantly updating list of shows, videos, or songs youâre most likely to click next.
This is about using AI to make online store products easier to findâboth in Google and inside your own siteâlike having a smart store clerk who instantly knows what each shopper wants and rearranges the shelves in real time.
Think of this as a super-smart billboard system that doesnât track who you are, but instead reads the page youâre on in real time and shows an ad that fits the exact topic, tone, and situation of that content.
This is like a smart accountant for your marketing budget: it watches all your ads and customer touchpoints and figures out which ones actually convinced people to buy, so you know where your money is really working.
Think of this as a playbook for law firms and inâhouse legal teams on how to safely and productively use tools like ChatGPT: where they help (drafting, summarising, research), where theyâre risky (confidentiality, hallucinations), and what changes in culture and process are needed so lawyers actually adopt them.
This is about using tools like ChatGPT inside and between government agencies so that routine paperwork, drafting, coordination, and information sharing between ministries and departments happen faster and more accurately, with the AI acting like a smart civil-service assistant that never sleeps.
This is like having a smart sales assistant that reads a prospectâs details in HubSpot and then drafts a personalized outreach email in Gmail for you, so reps just review, tweak if needed, and send.
Imagine a 24/7 security guard for your telecom network who has read every past fraud case, watches all current activity in real time, and can explain in plain language why something looks suspicious and what to do next. Thatâs what generative AI brings to fraud prevention: it doesnât just flag âweirdâ behavior, it also helps investigate, summarize, and respond to it much faster.
Think of this as turning your marketing team into pilots of a self-driving ad machine: humans set goals and guardrails, while AI continuously tests, tweaks, and reallocates budget across channels to get you more customers for less money.
Think of this like an autopilot for your online ads. Instead of humans constantly tweaking budgets, audiences, and creatives, AI watches performance in real time and automatically shifts spend to what works best so you get more sales for every advertising dollar.
Think of these AdTech AI agents as a team of tireless digital interns that understand ads, audiences, and campaign data. You tell them your goals (e.g., âget more app installs in Germany within this budgetâ), and they continuously research options, tweak settings, buy media, test creatives, and report backâwithout needing a human to click every button in every platform.
Imagine your marketing department had an endlessly energetic assistant that could draft ads, personalize messages for every customer, test which versions work best, and adjust campaigns on its own while your team focuses on strategy. Thatâs what generative AI is doing for marketing and advertising.
This is like giving your social media team a smart assistant that studies your followersâ behavior all day, figures out what they like, and then helps you decide what to post, when to post it, and who to show it to so your ads and content work better with less guesswork.
This is about using AI as a smart digital marketing assistant that creates, tests, and optimizes your online ads automatically so you sell more without manually tweaking every campaign.
Think of this as a tireless creative and analytics assistant that can draft campaigns, personalize messages for each customer, and learn from results to do better next timeâall in minutes instead of weeks.
Imagine a tireless junior director and writerâs room assistant that can instantly draft scenes, suggest dialogue, and explore alternate endings on command. Thatâs what this AI is for movie scriptsâit doesnât replace the director, but gives them a fast, idea-generating copilot.
This is like giving your online store a smart brain that watches how every shopper browses and buys, then quietly adjusts prices, search results, and recommendations so each person sees what theyâre most likely to want and buy.
This is like giving the mobile network its own team of smart digital engineers who constantly watch how itâs performing, spot problems early, and automatically fix or optimize things before customers notice.
Think of this as giving your marketing team a super-smart assistant that can study what every customer is doing in real time, write tailored messages for them, decide which ad to show where, and keep learning what works so your budget isnât wasted.
This is like having an AI assistant watch a live TV channel or livestream for you and take notes in real timeâwho is speaking, whatâs being said, topics, scenes, and key momentsâso people and systems can react instantly instead of waiting for manual review later.