Google just celebrated its 23rd birthday, recognising the company’s official founding on September 27th, 1998.
Over the course of its 23-year history, the search behemoth has influenced numerous facets of digital communication, web, and video consumption. In 1996, the search engine went live on Stanford’s network. Google Inc. was established in 1998. Larry Page and Sergey Brin, co-founders of Google, began the company as a research project on Stanford University‘s private network. Google grew from a single webpage to an online behemoth in 23 years. The following is a list of notable Google achievements.
- Google became a registered trademark in September 1998.
- Yahoo admits that Google’s search engine is superior in June 2000.
- Google rejected Yahoo’s $3 billion buyout bid in the summer of 2002.
- Gmail on April 1st, 2004.
- Google went public on April 29th, 2004.
- Google Maps on February 8th, 2005.
- Android in July of 2005, calling it the “best deal ever.”
- A year ago today: Google bought YouTube for $1.65 billion.
- DoubleClick on April 14th, 2007.
- The debut of the first Android phone took place on October 22nd, 2008.
- Google restructured and became Alphabet Inc. on August 10th, 2015.
- The Pixel was unveiled on October 20th, 2016, by Google.
- Google buys HTC on January 30th, 2018, for an undisclosed sum.
- Google’s search dominance irritates the US government on December 18th, 2020.
- Google’s own smartphone silicon was announced on August 2nd, 2021.
Google AI’s Major Project Milestones
Google AI is a Google subsidiary that focuses on artificial intelligence. Sundar Pichai, Google’s CEO, revealed it during Google I/O 2017.
- Serving cloud-based TPUs (tensor processing units) for machine learning software development.
- TensorFlow’s development.
- The TensorFlow Research Cloud will provide academics with a free cluster of 1,000 cloud TPUs to conduct machine learning studies on the condition that the research is open source and that the researchers publish their findings in a peer-reviewed scientific journal.
- A portal to approximately 5500 research articles by Google employees (as of September 2019).
- Magenta is a research team focused on deep learning that examines the role of machine learning as a tool in the creative process. The team launched a number of open source projects that enable artists and musicians to extend their processes through the use of artificial intelligence.
- Sycamore is a new programmable quantum processor with 54 qubits.
Here are a few of Google’s AI and machine learning-related products:
- Vertex AI: The new unified platform for machine learning will aid in the development, deployment, and scalability of better AI models.
- AI building blocks: Add sight, language, communication, and structured data to the applications in a matter of minutes.
- AutoML: Using Vertex AI’s vision, translation, and structured data capabilities, all powered by AutoML, to train high-quality custom machine learning models with little effort and knowledge in machine learning.
- AI Infrastructure: Cost-effectively train deep learning and machine learning models.
- Speech-to-Text: Convert speech to text accurately using a Google AI-powered API.
- Text-to-Speech: Convert text to natural-sounding speech using a Google AI-powered API.
- Virtual Agents: Allow users to access instant conversational self-service 24 hours a day, with seamless handoffs to human agents for more difficult situations.
- Agent Assist: Provide ongoing help to human agents during their contacts by detecting intent and delivering real-time, step-by-step advice.
- Natural Language: Utilise Google machine learning to extract insights from unstructured text.
- Healthcare Natural Language: Assisting healthcare workers in locating, evaluating, and connecting medical knowledge contained in text data.
- Recommendations AI: At scale, deliver highly tailored product suggestions.
The transformation of Google from a simple webpage to a digital behemoth in a little more than two decades has been nothing short of remarkable.
Subscribe to our NewsletterGet the latest updates and relevant offers by sharing your email.
Nivash has a doctorate in Information Technology. He has worked as a Research Associate at a University and as a Development Engineer in the IT Industry. He is passionate about data science and machine learning.