In a recent article, OpenAI expressed its commitment to creating AI that is both safe and helpful. OpenAI’s most recent model, GPT-4, can boost creativity, increase productivity and offer personalized learning opportunities.
OpenAI does, however, recognize that there are risks associated with AI technologies, which must be managed through deployment practices and safety precautions.
Here are the steps the business is taking to reduce such risks:
OpenAI’s article has, however, caused a bit of controversy on Twitter, with users criticizing OpenAI for not addressing existential risks and recklessly focussing on commercialization instead. Users also expressed that the article is insincere as OpenAI fails to tackle the real problems by keeping its commitments vague and implementing inadequate security solutions.
For more insights, visit Search Engine Journal here.
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Italian Government Bans ChatGPT: OpenAI was recently forced to shut down its applications to Italian users as the Garante per la protezione dei dati personali (Guarantor for the protection of personal data) conducts an investigation for certain violations. The Italian government worries that other countries are not using personal information responsibly, nor are younger audiences’ safety being prioritized. OpenAI is expected to abide by Italy’s Personal Data Protection Code, even though it is based in the States. The allegations include users not being adequately informed of personal data collection and that OpenAI could not provide reasoning as to why it needed to collect personal information. Additionally, OpenAI did not request age verification for content suitable for older age groups or require parental consent. It is also of the opinion that ChatGPT does not process personal information correctly or use real facts. For more insights, visit Search Engine Journal here.
Google Search CEO, Sundar Pichai, Confirms Conversational AI Coming Soon: Large language models (LLMs) may eventually be included in Google search results. Sundar Pichai, CEO of Google, promises that conversational artificial intelligence (AI) will eventually arrive in Search, despite its absence as of yet. Even while the new BingGPT search with integrated AI conversation was eagerly anticipated, the growth in search engine market share it has so far produced has been minimal. The major questions we’re all eager to have answered when Google incorporates dialogue driven by AI into search are the following: What kind of impact will it have on Google’s organic traffic flow?, and Would it affect the return on investment (ROI) for businesses and organizations using Google Adwords? In an interview with the Wall Street Journal, Pichai said that people would be able to ask Google questions and interact with large language models regarding Search. Google is currently testing various search products that let users ask follow-up questions. According to Pichai, chatbots don’t threaten Google’s search business because they provide a more significant opportunity space. For more details, visit Search Engine Land here.
Google Shows How It Detects Fake Business Reviews: Google recently published a report stating how it determines whether business profiles and reviews are real or fake. Google’s machine learning systems have been optimized to find and remove fake listings, business reviews as well as fraudulent videos and images. Since 2021, Google has “increased the number of removals by 20%, removing 200 million photos and 7 million videos and blocked or removed over 115 million reviews,” according to an article by Search Engine Journal. Google’s new machine learning models look out for unusual patterns in user behavior regarding content contribution. Google’s systems review new content before being posted and scan published content using the updated machine learning model in case anything has slipped through the initial review stage. Google also scans images to find any overlaid content that diverts phone calls from legitimate businesses to scammers. It also scans for word patterns, bots and duplicate content as well as identifies misleading content using a system called “intelligent text matching.” Read more about how Google plans to tackle fake review contributions here.
Tutorial on How To Analyze Traffic Drops in Google Search Console: Google’s Search Advocate, Daniel Waisberg, provides helpful advice on how to rapidly identify and assess the causes of a reduction in Google Search traffic in a YouTube video. After the recent March 2023 broad core algorithm update, many people are currently assessing how it may affect their websites. So this comprehensive guide comes at the perfect time. The Search Console Performance report is a great place to start if you’re attempting to determine how the change has affected your site. There are various reasons for drops in organic traffic like technical issues, algorithm updates, manual actions, Search interest disruption, reporting glitches and seasonality effects. Search Console Performance Report is a great tool to understand these fluctuations in traffic. Waisberg offers different approaches for studying the data: To put the drop in perspective and spot any patterns or trends, increase the date range to 16 months. To have access to information going back more than 16 months, periodically export and store data. To identify the precise changes, contrast the drop period with a comparable period (such as the same month last year or the same day last week). Examine every tab to see if changes only applied to particular searches, pages, nations, devices, or Search appearances. Make sure to compare the same number of days and, if possible, the same weekdays. To determine whether the decline just affected the Search, Google Images, Video, or News tabs, analyze each category of Search independently. Read more on how to analyze Search Console traffic drops here.
Google Bard Updated To Include Logic and Math Responses: Recently, Google has implemented some improvements to its AI chatbot, Bard – it can now provide answers in math and logic thanks to the incorporation of Google’s Pathways Language Model, PaLM. It has 540 billion parameters with an additional 8 billion and 62 billion smaller parameter models to test its model scale effects. Jack Krawczyk, the Google executive in charge of Bard and Google’s AI initiatives, posted on Twitter, “Today I wanted to report that we’ve increased Bard’s skills in arithmetic and logic by incorporating some of the gains we’ve gained in PaLM.” According to Krawczyk, Bard can now comprehend and react to your instructions, offering better inquiry capabilities when presented with multi-step arithmetic problems and multi-step word problems. What’s more, Bard will soon also offer coding, Krawczyk continued. For more insights, visit Search Engine Land here.
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