Technology
25 Biggest Moments in Search, From Helpful Images to AI
Here’s how we’ve made Search more helpful over 25 years — and had a little fun along the way, too.
When Google first launched 25 years ago, it was far from the first search engine. But quickly, Google Search became known for our ability to help connect people to the exact information they were looking for, faster than they ever thought possible.
Over the years, we’ve continued to innovate and make Google Search better every day. From creating entirely new ways to search, to helping millions of businesses connect with customers through search listings and ads (starting with a local lobster business advertising via AdWords in 2001), to having some fun with Doodles and easter eggs — it’s been quite a journey.
For our 25th birthday, we’re looking back at some of the milestones that made Google more helpful in the moments that matter, and played a big role in where Google is today. Learn more about our history in our Search Through Time site.
2001: Google Images
When Jennifer Lopez attended the 2000 Grammy Awards, her daring Versace dress became an instant fashion legend — and the most popular query on Google at the time. Back then, search results were just a list of blue links, so people couldn’t easily find the picture they were looking for. This inspired us to create Google Images.
2001: “Did you mean?”
“Did you mean,” with suggested spelling corrections, was one of our first applications of machine learning. Previously, if your search had a misspelling (like “floorescent”), we’d help you find other pages that had the same misspelling, which aren’t usually the best pages on the topic. Over the years we’ve developed new AI-powered techniques to ensure that even if your finger slips on the keyboard, you can find what you need.

2002: Google News
During the tragic events of September 11, 2001, people struggled to find timely information in Search. To meet the need for real-time news, we launched Google News the following year with links to a diverse set of sources for any given story.
2003: Easter eggs
Googlers have developed many clever Easter eggs hidden in Search over the years. In 2003, one of our first Easter eggs gave the answer to life, the universe and everything, and since then millions of people have turned their pages askew, done a barrel roll, enjoyed a funny recursive loop and celebrated moments in pop culture.

One of our earliest Easter eggs is still available on Search.
2004: Autocomplete
Wouldn’t it be nice to type as quickly as you think? Cue Autocomplete: a feature first launched as “Google Suggest” that automatically predicts queries in the search bar as you start typing. Today, on average, Autocomplete reduces typing by 25% and saves an estimated over 200 years of typing time per day.
2004: Local information
People used to rely on traditional phone books for business information. The web paved the way for local discovery, like “pizza in Chicago” or “haircut 75001.” In 2004, Google Local added relevant information to business listings like maps, directions and reviews. In 2011, we added click to call on mobile, making it easy to get in touch with businesses while you’re on the go. On average, local results in Search drive more than 6.5 billion connections for businesses every month, including phone calls, directions, ordering food and making reservations.
2006: Google Translate
Google researchers started developing machine translation technology in 2002 to tackle language barriers online. Four years later, we launched Google Translate with text translations between Arabic and English. Today, Google Translate supports more than 100 languages, with 24 added last year.

2006: Google Trends
Google Trends was built to help us understand trends on Search with aggregated data (and create our annual Year in Search). Today, Google Trends is the world’s largest free dataset of its kind, enabling journalists, researchers, scholars and brands to learn how searches change over time.
2007: Universal Search
Helpful search results should include relevant information across formats, like links, images, videos, and local results. So we redesigned our systems to search all of the content types at once, decide when and where results should blend in, and deliver results in a clear and intuitive way. The result, Universal Search, was our most radical change to Search at the time.
2008: Google Mobile App
With the arrival of Apple’s App Store, we launched our first Google Mobile App on iPhone. Features like Autocomplete and “My Location” made search easier with fewer key presses, and were especially helpful on smaller screens. Today, there’s so much you can do with the Google app — available on both Android and iOS — from getting help with your math homework with Lens to accessing visual translation tools in just a tap.
2008: Voice Search
In 2008, we introduced the ability to search by voice on the Google Mobile App, expanding to desktop in 2011. With Voice Search, people can search by voice with the touch of a button. Today, search by voice is particularly popular in India, where the percentage of Indians doing daily voice queries is nearly twice the global average.

2009: Emergency Hotlines
Following a suggestion from a mother who had a hard time finding poison control information after her daughter swallowed something potentially dangerous, we created a box for the poison control hotline at the top of the search results page. Since this launch, we’ve elevated emergency hotlines for critical moments in need like suicide prevention.
2011: Search by Image
Sometimes, what you’re searching for can be hard to describe with words. So we launched Search by Image so you can upload any picture or image URL, find out what it is and where else that image is on the web. This update paved the way for Lens later on.
2012: Knowledge Graph
We introduced the Knowledge Graph, a vast collection of people, places and things in the world and how they’re related to one another, to make it easier to get quick answers. Knowledge Panels, the first feature powered by the Knowledge Graph, give you a quick snapshot of information about topics like celebrities, cities and sports teams.

2015: Popular Times: We launched the Popular Times feature in Search and Maps to help people see the busiest times of the day when they search for places like restaurants, stores, and museums.
2016: Discover
By launching a personalized feed (now called Discover) we helped people explore content tailored to their interests right in the Google app, without having to search.
2017: Lens
Google Lens turns your camera into a search query by looking at objects in a picture, comparing them to other images, and ranking those other images based on their similarity and relevance to the original picture. Now, you can search what you see in the Google app. Today, Lens sees more than 12 billion visual searches per month.
2018: Flood forecasting
To help people better prepare for impending floods, we created forecasting models that predict when and where devastating floods will occur with AI. We started these efforts in India and today, we’ve expanded flood warnings to 80 countries.

2019: BERT
A big part of what makes Search helpful is our ability to understand language. In 2018, we introduced and open-sourced a neural network-based technique to train our language understanding models: BERT (Bidirectional Encoder Representations from Transformers). BERT makes Search more helpful by better understanding language, meaning it considers the full context of a word. After rigorous testing in 2019, we applied BERT to more than 70 languages. Learn more about how BERT works to understand your searches.
2020: Shopping Graph
Online shopping became a whole lot easier and more comprehensive when we made it free for any retailer or brand to show their products on Google. We also introduced Shopping Graph, an AI-powered dataset of constantly-updating products, sellers, brands, reviews and local inventory that today consists of 35 billion product listings.
2020: Hum to Search
We launched Hum to Search in the Google app, so you’ll no longer be frustrated when you can’t remember the tune that’s stuck in your head. The machine learning feature identifies potential song matches after you hum, whistle or sing a melody. You can then explore information on the song and artist.
2021: About this result
To help people make more informed decisions about which results will be most useful and reliable for them, we added “About this result” next to most search results. It explains why a result is being shown to you and gives more context about the content and its source, based on best practices from information literacy experts. ‘About this’ result is now available in all languages where Search is available.
2022: Multisearch
To help you uncover the information you’re looking for — no matter how tricky — we created an entirely new way to search with text and images simultaneously through Multisearch. Now you can snap a photo of your dining set and add the query “coffee table” to find a matching table. First launched in the U.S., Multisearch is now available globally on mobile, in all languages and countries where Lens is available.
2023: Search Labs & Search Generative Experience (SGE)
Every year in Search, we do hundreds of thousands of experiments to figure out how to make Google more helpful for you. With Search Labs, you can test early-stage experiments and share feedback directly with the teams working on them. The first experiment, SGE, brings the power of generative AI directly into Search. You can get the gist of a topic with AI-powered overviews, pointers to explore more and natural ways to ask follow ups. Since launching in the U.S., we’ve rapidly added new capabilities, with more to come.
As someone who’s been following the world of search engines for more than two decades, it’s amazing to reflect on where Google started — and how far we’ve come.
Technology
Leticia Otomewo Becomes Secure Electronic Technology’s Acting Secretary
By Aduragbemi Omiyale
One of the players in the Nigerian gaming industry, Secure Electronic Technology (SET) Plc, has appointed Ms Leticia Otomewo as its acting secretary.
This followed the expiration of the company’s service contract with the former occupier of the seat, Ms Irene Attoe, on January 31, 2026.
A statement to the Nigerian Exchange (NGX) Limited on Thursday said Ms Otomewo would remain the organisation’s scribe in an acting capacity, pending the ratification and appointment of a substantive company secretary at the next board meeting.
She was described in the notice signed by the Managing Director of the firm, Mr Oyeyemi Olusoji, as “a results-driven executive with 22 years of experience in driving business growth, leading high-performing teams, and delivering innovative solutions.”
The acting secretary is also said to be “a collaborative leader with a passion for mentoring and developing talent.”
“The company assures the investing public that all Company Secretariat responsibilities and regulatory obligations will continue to be discharged in full compliance with the Companies and Allied Matters Act, applicable regulations, and the Nigerian Exchange Limited Listing Rules,” the disclosure assured.
Meanwhile, the board thanked Ms Attoe “for professionalism and contributions to the Company during the period of her engagement and wishes her well in her future endeavours.”
Technology
Russia Blocks WhatsApp Messaging Service
By Adedapo Adesanya
The Russian government on Thursday confirmed it has blocked the WhatsApp messaging service, as it moves to further control information flow in the country.
It urged Russians to use a new state-backed platform called Max instead of the Meta-owned service.
WhatsApp issued a statement earlier saying Russia had attempted to “fully block” its messaging service in the country to force people toward Max, which it described as a “surveillance app.”
“Today the Russian government attempted to fully block WhatsApp in an effort to drive people to a state-owned surveillance app,” WhatsApp posted on social media platform X.
“Trying to isolate over 100 million users from private and secure communication is a backwards step and can only lead to less safety for people in Russia,” it said, adding: “We continue to do everything we can to keep users connected.”
Russia’s latest move against social media platforms and messaging services like WhatsApp, Signal and Telegram comes amid a wider attempt to drive users toward domestic and more easily controlled and monitored services, such as Max.
Russia’s telecoms watchdog, Roskomnadzor, has accused messaging apps Telegram and WhatsApp of failing to comply with Russian legislation requiring companies to store Russian users’ data inside the country, and of failing to introduce measures to stop their platforms from being used for allegedly criminal or terrorist purposes.
It has used this as a basis for slowing down or blocking their operations, with restrictions coming into force since last year.
For Telegram, it may be next, but so far the Russian government has been admittedly slowing down its operations “due to the fact that the company isn’t complying with the requirements of Russian legislation.”
The chat service, founded by Russian developers but headquartered in Dubai, has been a principal target for Roskomnadzor’s scrutiny and increasing restrictions, with users reporting sluggish performance on the app since January.
Technology
Nigerian AI Startup Decide Ranks Fourth Globally for Spreadsheet Accuracy
By Adedapo Adesanya
Nigerian startup, Decide, has emerged as the fourth most accurate Artificial Intelligence (AI) agent for spreadsheet tasks globally, according to results from SpreadsheetBench, a widely referenced benchmark for evaluating AI performance on real-world spreadsheet problems.
According to the founder, Mr Abiodun Adetona, the ranking places Decide alongside well-funded global AI startups, including Microsoft, OpenAI, and Anthropic.
Mr Adetona, an ex-Flutterwave developer, also revealed that Decide now has over 3,000 users, including some who are paying customers, a signal to the ability of the startup to scale in the near future.
SpreadsheetBench is a comprehensive evaluation framework designed to push Large Language Models (LLMs) to their limits in understanding and manipulating spreadsheet data. While many benchmarks focus on simple table QA, SpreadsheetBench treats a spreadsheet as a complex ecosystem involving spatial layouts, formulas, and multi-step reasoning. So far, only three agents rank higher than Decide, namely Nobie Agent, Shortcut.ai, and Qingqiu Agent.
Mr Adetona said SpreadsheetBench measures how well AI agents can handle practical spreadsheet tasks such as writing formulas, cleaning messy data, working across multiple sheets, and reasoning through complex Excel workflows. Decide recorded an 82.5% accuracy score, solving 330 out of 400 verified tasks.
“The result reflects sustained investment in applied research, product iteration, and learning from real-world spreadsheet workloads across a wide range of use cases,” Mr Adetona told Business Post.
For Mr Adetona, who built Decide out of frustration with how much time professionals spend manually cleaning data, debugging formulas, and moving between sheets, “This milestone highlights how focused engineering and domain-specific AI development can deliver frontier-level performance outside of large research organisations. By concentrating on practical business data problems and building systems grounded in real user environments, we believe smaller teams can contribute meaningfully to advancing applied AI.”
“For Decide, this is a foundation for continued progress in intelligent spreadsheet and analytics automation,” he added.
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