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AI’s Revolutionary Effects on Startups’ Patent Analysis

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AI's Revolutionary Effects on Startups' Patent Analysis

Every startup is eager to introduce the world to its next big idea. Additionally, it’s always a good idea to file for a patent in order to protect their concept from being copied or corrupted. Since patents are by definition unique, entrepreneurs must be absolutely convinced that their concept is unique before applying for one. This can be achieved by performing an exhaustive patent search beforehand. Since speed and accuracy are critical, AI has a strong case to accelerate the patent search process for startups.

The Value of Searching for and Analyzing Patents

  • One useful method for learning about market trends is to study the patent applications that are currently pending. If a single product category has several patents, it may be a competitive market meeting different consumer requirements in that industry. Finding potential technological gaps and uncharted territory is another benefit of conducting a search and analysis of patents. For example, the firm may discover that while their initial concept has been investigated, there is a chance to safeguard and market a complementary product that would appeal to the same customer base.
  • Startups can save time and money by performing a preliminary patent search to make sure that (a) their idea is not already patented or a commercial product, or (b) it does not fall under a class of products that is not eligible for patent protection. They will save the expenses and future legal headaches of having to deal with patent infringement because of this.

Recognizing The Difficulties in Doing A Patent Search

  • In every industry, searching for patents is an extremely intricate and time-consuming procedure. It is necessary to create intricate Boolean searches, sift through all of the available patent data, and identify the key elements—such as highlighting murky areas that should be sent to a lawyer for advice. In terms of taking advantage of current market opportunities, this can be counterproductive because it can take a long time.
  • It is impossible to overestimate the importance of precision in patent searches and the analysis that follows. Any inaccuracy could result in the rejection of the patent, lawsuits alleging patent infringement, and a substantial loss of time and money. assessing whether the proposed invention is simply a copy of an existing filing made by someone else, or a version with discernible variations, becomes more challenging when assessing the criteria for patent duplication.

Artificial Intelligence in Patent Analysis and Search

  • Artificial intelligence is considerably faster than humans at finding and analyzing any type of data. Previous natural language search engines were unable to decipher the meaning and intention contained in the user-provided innovation description. However, AI-driven patent search has matured and can now produce significantly improved search relevance and extremely accurate results thanks to pre-trained Large Language Models. As a result, it is the perfect solution for tasks that require a lot of time, including patent search and analysis. Startups are already moving more quickly and closer to their eventual patent registration with the help of a number of AI search and result analysis tools.
  • Search efficiency: The efficiency that AI offers to the search process is its most evident benefit. The user may “rely” on the AI search system to provide extremely accurate results in a matter of seconds, saving them the trouble of manually crafting complex search terms to comb through patent data.
  • Semantic assessments of patents can be performed by AI trained in natural language processing (NLP). This helps them to appropriately read any sections with ambiguous wording and make sense of regional variations in language. This is especially helpful when examining patent claims for various iterations of the same invention.
  • Classification algorithms: Not all patent-related information is probably arranged according to how the startup in question views the technology. The end user can be presented with a rated and classed result by training machine learning algorithms to sort the data based on relevance.
  • Visualization tools: AI can classify and highlight important information in an understandable visual report by organizing and summarizing the data. Making educated decisions and presenting findings to pertinent parties would be made simpler as a result.

AI’s Future Directions for Searching and Analyzing Patents

Artificial intelligence has many uses in the analysis and search of patents. In order to establish a single, transparent chain of information, the integration of AI with blockchain and IoT is now being investigated. Even while some of these AI apps can be pricey, new choices are being created daily, so in the end, costs will be reduced for startups with tight budgets. AI algorithms are just getting started, but they have the potential to speed up the patent registration process enormously, so firms who use them now will be the first to see their innovative ideas come to fruition.

PatSeer is an AI-based patent search engine that leads the way in innovation by allowing users to navigate the IP landscape with never-before-seen ease thanks to its rich Boolean and AI search functionalities. With the platform’s easy-to-use interface, startups can do thorough patent searches to make sure their ideas are original and eligible for patent protection.

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Biden, Kishida Secure Support from Amazon and Nvidia for $50 Million Joint AI Research Program

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As the two countries seek to enhance cooperation around the rapidly advancing technology, President Joe Biden and Japanese Prime Minister Fumio Kishida have enlisted Amazon.com Inc. and Nvidia Corp. to fund a new joint artificial intelligence research program.

A senior US official briefed reporters prior to Wednesday’s official visit at the White House, stating that the $50 million project will be a collaborative effort between Tsukuba University outside of Tokyo and the University of Washington in Seattle. A separate collaborative AI research program between Carnegie Mellon University in Pittsburgh and Tokyo’s Keio University is also being planned by the two nations.

The push for greater research into artificial intelligence comes as the Biden administration is weighing a series of new regulations designed to minimize the risks of AI technology, which has developed as a key focus for tech companies. The White House announced late last month that federal agencies have until the end of the year to determine how they will assess, test, and monitor the impact of government use of AI technology.

In addition to the university-led projects, Microsoft Corp. announced on Tuesday that it would invest $2.9 billion to expand its cloud computing and artificial intelligence infrastructure in Japan. Brad Smith, the president of Microsoft, met with Kishida on Tuesday. The company released a statement announcing its intention to establish a new AI and robotics lab in Japan.

Kishida, the second-largest economy in Asia, urged American business executives to invest more in Japan’s developing technologies on Tuesday.

“Your investments will enable Japan’s economic growth — which will also be capital for more investments from Japan to the US,” Kishida said at a roundtable with business leaders in Washington.

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OnePlus and OPPO Collaborate with Google to Introduce Gemini Models for Enhanced Smartphone AI

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As anticipated, original equipment manufacturers, or OEMs, are heavily integrating AI into their products. Google is working with OnePlus, OPPO, and other companies to integrate Gemini models into their smartphones. They intend to introduce the Gemini models on smartphones later this year, becoming the first OEMs to do so. Gemini models will go on sale later in 2024, as announced at the Google Cloud Next 24 event. Gemini models are designed to provide users with an enhanced artificial intelligence (AI) experience on their gadgets.

Customers in China can now create AI content on-the-go with devices like the OnePlus 12 and OPPO Find X7 thanks to OnePlus and OPPO’s Generative AI models.

The AI Eraser tool was recently made available to all OnePlus customers worldwide. This AI-powered tool lets users remove unwanted objects from their photos. For OnePlus and OPPO, AI Eraser is only the beginning.

In the future, the businesses hope to add more AI-powered features like creating original social media content and summarizing news stories and audio.

AndesGPT LLM from OnePlus and OPPO powers AI Eraser. Even though the Samsung Galaxy S24 and Google Pixel 8 series already have this feature, it is still encouraging to see OnePlus and OPPO taking the initiative to include AI capabilities in their products.

OnePlus and OPPO devices will be able to provide customers with a more comprehensive and sophisticated AI experience with the release of the Gemini models. It is important to remember that OnePlus and OPPO already power the Trinity Engine, which makes using phones incredibly smooth, and use AI and computational mathematics to enhance mobile photography.

By 2024, more original equipment manufacturers should have AI capabilities on their products. This is probably going to help Google because OEMs will use Gemini as the foundation upon which to build their features.

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Meta Explores AI-Enabled Search Bar on Instagram

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In an attempt to expand the user base for its generative AI-powered products, Meta is moving forward. The business is experimenting with inserting Meta AI into the Instagram search bar for both chat with AI and content discovery, in addition to testing the chatbot Meta AI with users in nations like India on WhatsApp.

When you type a query into the search bar, Meta AI initiates a direct message (DM) exchange in which you can ask questions or respond to pre-programmed prompts. Aravind Srinivas, CEO of Perplexity AI, pointed out that the prompt screen’s design is similar to the startup’s search screen.

Plus, it might make it easier for you to find fresh Instagram content. As demonstrated in a user-posted video on Threads, you can search for Reels related to a particular topic by tapping on a prompt such as “Beautiful Maui sunset Reels.”

Additionally, TechCrunch spoke with a few users who had the ability to instruct Meta AI to look for recommendations for Reels.

By using generative AI to surface new content from networks like Instagram, Meta hopes to go beyond text generation.

With TechCrunch, Meta verified the results of its Instagram AI experiment. But the company didn’t say whether or not it uses generative AI technology for search.

A Meta representative told TechCrunch, “We’re testing a range of our generative AI-powered experiences publicly in a limited capacity. They are under development in varying phases.”

There are a ton of posts available discussing Instagram search quality. It is therefore not surprising that Meta would want to enhance search through the use of generative AI.

Furthermore, Instagram should be easier to find than TikTok, according to Meta. In order to display results from Reddit and TikTok, Google unveiled a new perspectives feature last year. Instagram is developing a feature called “Visibility off Instagram” that could allow posts to appear in search engine results, according to reverse engineer Alessandro Paluzzi, who made this discovery earlier this week on X.

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