Top Natural Language Processing Tools and Libraries for Data Scientists

It is widely used in production environments because of its efficiency and speed. Apple’s AI study shows that changing trivial variables in math problems that wouldn’t fool kids or adding text that doesn’t alter how you’d solve the problem can significantly impact the reasoning performance of large language models. If a customer asks for the latest news about a company, for instance, the system queries recent news documents. You can foun additiona information about ai customer service and artificial intelligence and NLP. On the other hand, if the question is about stock performance, the model accesses structured financial data to provide the current stock price and trends. The ability to reason about which tool to call upon demonstrates the system’s agentic capabilities.

Bengaluru-based BharatGPT maker startup CoRover.ai serves over a billion users with its LLM-based conversational AI platform, offering text, audio, and video agents in over 100 languages. Supported by NVIDIA Inception, CoRover powers virtual assistants for clients like Indian Railways on many of its customer platforms. He added that as businesses explore new models, synthetic data too becomes essential, enabling continuous model improvement.

Instead, they’re simply matching patterns from their training data sets. But that’s only because they’ve seen similar problems and can predict the answer. In this case, the training data set is not optimally aligned with the target group and chatbot datasets does not represent it. In this case, the AI systems have been trained too much on the data set. You must always keep an eye on overfitting and make sure that the training data set and the AI training itself are aligned with each other.

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Fluid AI, a Mumbai-based startup, provides generative AI chatbots, voice bots, and APIs to enhance enterprise efficiency. These tools leverage an organisation’s knowledge base to deliver insights, reports, and accurate answers. Fluid AI’s chatbots improve customer service by boosting agent productivity and reducing response times with real-time outputs.

Natural Language Processing (NLP) is a rapidly evolving field in artificial intelligence (AI) that enables machines to understand, interpret, and generate human language. NLP is integral to applications such as chatbots, sentiment analysis, translation, and search engines. Data scientists leverage a variety of tools and libraries to perform NLP tasks effectively, each offering unique features suited to specific challenges. Here is a detailed look at some of the top NLP tools and libraries available today, which empower data scientists to build robust language models and applications. Now, amid a wave of broader interest in applications for artificial intelligence, some dog researchers are hoping that AI might provide answers. ChatGPT is able to respond in language that seems human, because it has been trained on massive datasets of writing, which it then mimics in its responses.

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A similar premise applies to other generative-AI programs; large language models identify patterns in the data they’re fed, map relationships among them, and produce outputs accordingly. Wilson leads product strategy, product management, product marketing, and research at Exabeam. He is a leader and innovator in AI, cybersecurity, and cloud computing, with over 20 years of experience leading high-performance teams to build mission-critical enterprise software and high-leverage platforms. Before joining Exabeam, he served as CPO at Contrast Security leading all aspects of product development, including strategy, product management, product marketing, product design, and engineering. Wilson has a proven track record of driving product transformation from on-premises legacy software to subscription-based SaaS business models including at Citrix, accounting for over $1 billion in ARR. He also has experience building software platforms at multi-billion-dollar technology companies including Oracle and Sun Microsystems.

• From a societal perspective, it would be helpful if people consider what they upload to the EPR and also have the social benefits clearly communicated to them.
• Apple’s study, available as a pre-print version at this link, details the types of experiments the researchers ran to see how the reasoning performance of various LLMs would vary.
• It rapidly passed a million users – albeit, with the numbers likely inflated by those trying to entice the chatbot into making scurrilous, inappropriate, or taboo pronouncements.
• With AI-powered algorithms, agents can understand their clients better, anticipate their needs and provide personalized policies that are more likely to appeal to them.
• Diet is also a factor, but other living conditions such as the climate are also decisive.
• The result should be identical in both cases, but the LLMs subtracted the smaller kiwis from the total.

While NLTK and TextBlob are suited for beginners and simpler applications, spaCy and Transformers by Hugging Face provide industrial-grade solutions. AllenNLP and fastText cater to deep learning and high-speed requirements, respectively, while Gensim specializes in topic modelling and document similarity. Choosing the right tool depends on the project’s complexity, resource availability, and specific NLP requirements. “This new service applies cloud technology in a new way for large data packages, allowing users to significantly scale performance and maximize data value,” said Boris Skopljak, vice president, geospatial at Trimble, in the release. “With this launch, we are a step closer to realizing living digital twins and artificial intelligence applications at scale.”

This Apple AI study suggests ChatGPT and other chatbots can’t actually reason

Every build is by definition a moving target, with specs and progress status changing daily. Science certainly needs to take a step towards society here and also push ahead with science communication, also to reduce data protection concerns. Here too, quality assurance of the data or appropriately adapted data management in the projects would be important. You definitely need a good national database, but you can also benefit greatly from international data. So far, however, the data situation in the healthcare sector in Germany is rather miserable.

The diverse ecosystem of NLP tools and libraries allows data scientists to tackle a wide range of language processing challenges. From basic text analysis to advanced language generation, these tools enable the development of applications that can understand and respond to human language. With continued advancements in NLP, the future holds even more powerful tools, enhancing the capabilities of data scientists in creating smarter, language-aware applications.

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VideoVerse, based in Mumbai with global offices, uses AI to revolutionise sports media content creation, serving clients like the Indian Premier League and Vietnam Basketball Association. At NVIDIA AI Summit 2024, around 50 Indian startups are showcasing their AI innovations, with panels, pitches, and insights from venture capital firms. NVIDIA’s Inception program, launched in 2016, is a virtual incubator designed to support startups with ideas in AI and data science. BGR’s audience craves our industry-leading insights on the latest in tech and entertainment, as well as our authoritative and expansive reviews. Chris Smith has been covering consumer electronics ever since the iPhone revolutionized the industry in 2008.

On Wednesday, Tel Aviv-based construction technology provider Buildots announced the launch of Dot, a plain language chatbot that gives up-to-date answers about project details. From a chatbot that speaks builders’ language to tech that corrals massive amounts of data captured from scans, this month’s offerings are aimed at simplifying complex tasks. Maintaining the integrity and efficacy of AI systems requires regular monitoring and updating of security protocols. Enhancing accountability for humans involved in the process and increasing transparency can build trust and improve oversight of AI operations. Additionally, it ensures the ethical and responsible use of AI across networks and throughout the enterprise.

Time and again, studies show that decisions made by AI systems for these groups of people in the healthcare sector are significantly worse. The bias in the data basis is then of course automatically transferred to AI systems and their recommendations. Gender in particular and aspects such as ethnic origin ChatGPT are sources of AI bias. But it can be said that there is hardly any data set that is completely free of bias. The data that is available in the health sector is mainly that of heterosexual, older, white men. A solid database is of great importance for AI training, especially in the healthcare sector.

The results of this experiment are detailed in a paper published in Nature today. Currently SynthID for text only works on content generated by Google’s models, but the hope is that open-sourcing it will ChatGPT App expand the range of tools it’s compatible with. Karya’s efforts help accelerate AI development for non-English speakers, using NVIDIA’s NeMo and NIM platforms to build custom AI models for businesses.

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Google and DeepMind have developed an artificial intelligence-powered chatbot tool called Med-PaLM designed to generate “safe and helpful answers” to questions posed by healthcare professionals and patients. Researchers have used similar approaches to study dog communication since at least 2006, but AI has recently gotten far better at processing huge amounts of data. Don’t expect to discuss the philosophy of Immanuel Kant with Fido over coffee anytime soon, however. It’s still early days, and researchers don’t know what kind of breakthroughs AI could deliver—if any at all. “It’s got huge potential—but the gap between the potential and the actuality hasn’t quite emerged yet,” Vanessa Woods, a dog-cognition expert at Duke University, told me.

In a competitive market where speed is often a critical factor, this can give agents a significant edge. Superintendents can use Dot to guide subcontractors by cross-referencing conditions and ensuring multiple prerequisites are met before starting new tasks. For instance, a superintendent might ask, “Give me a list of apartments where drywall closure is completed but bathroom tiling hasn’t started,” enabling them to prioritize the right tasks and allocate resources efficiently, the firm says. From a societal perspective, it would be helpful if people consider what they upload to the EPR and also have the social benefits clearly communicated to them. It would be ideal if data collection in the ePA were integrated into the various processes as automatically as possible. Filling the EPR must not become an additional burden for patients or the various healthcare professions.

In 2018, it was revealed that the company harvested millions of Facebook profiles of US voters, in one of the tech giant’s biggest ever data breaches, and used them to build a powerful software program to influence elections. The new tool leverages Buildots’ comprehensive dataset and generative artificial intelligence to provide instant insights in response to direct questions, according to the news release. The tool, called SynthID, is part of a larger family of watermarking tools for generative AI outputs.

To detect the watermark and determine whether text has been generated by an AI tool, SynthID compares the expected probability scores for words in watermarked and unwatermarked text. Google DeepMind has developed a tool for identifying AI-generated text and is making it available open source. The company conducted a massive experiment on its watermarking tool SynthID’s usefulness by letting millions of Gemini users rank it. These risks must be carefully managed to ensure the safe and ethical use of AI technologies. Addressing these issues is crucial to harnessing the full potential of AI while safeguarding sensitive information, promoting fairness, and ensuring system integrity. Unlike hallucinations – where the AI mistakenly generates false information – deepfakes are intentionally designed to deceive.

“By fairly compensating these communities for their digital work, we are able to boost their quality of life while supporting the creation of multilingual AI tools they’ll be able to use in the future,” said Manu Chopra, CEO of Karya. We guide our loyal readers to some of the best products, latest trends, and most engaging stories with non-stop coverage, available across all major news platforms. Adding these “seemingly relevant but ultimately inconsequential statements” to GSM-Symbolic templates leads to “catastrophic performance drops” for the LLMs. Even o1-preview struggled, showing a 17.5% performance drop compared to GSM8K. The result should be identical in both cases, but the LLMs subtracted the smaller kiwis from the total. Apparently, you don’t count the smaller fruit if you’re an AI with reasoning abilities.

• Its AI-powered platform, Magnifi, generates game highlights up to 15x faster, boosting viewership and enabling smaller sports like longball and kabaddi to grow their fanbase on limited budgets.
• This is because a lot of data is generated in intensive care units, as patients’ vital signs are monitored extensively and continuously.
• The company uses NVIDIA’s NIM microservices, NeMo platform, and TensorRT inference engine to offer scalable, custom AI solutions.
• One famous example is Cambridge Analytica, the data analytics firm that worked with Donald Trump’s election team and the winning Brexit campaign.

According to Gultekin, while general-purpose models offer flexibility, task-specific models are favoured for efficiency in areas such as sentiment analysis and classification. The future of AI, according to Gultekin, points toward autonomous agentic systems, which can perform tasks independently with minimal human involvement, unlocking new productivity levels. Snowflake also integrates agentic AI systems that refine queries to ensure accuracy and align answers with user intent. They operate independently, choosing tools and data sources as needed, such as retrieving stock prices or news documents, showcasing early-stage autonomy. “Instead of waiting days for analysts to respond to dashboard queries, their AI-powered chatbot provides real-time answers, streamlining decision-making,” Gulketin explained.

Meanwhile, hucksters posing as dog whisperers and pet psychics have happily taken their cash by claiming to be able to help them translate their dogs’ inner thoughts. AI is skilled at tapping into vast realms of data and tailoring it to a specific purpose—making it a highly customizable tool for combating misinformation. There is another benefit too, says João Gante, a machine-learning engineer at Hugging Face. Open-sourcing the tool means anyone can grab the code and incorporate watermarking into their model with no strings attached, Gante says. This will improve the watermark’s privacy, as only the owner will know its cryptographic secrets.

Troy Nichols, assistant safety director at Ogden, Utah-based contractor Wadman Corp. and a Safety AI user, said in the release he likes the extra set of eyes. “I’m not at the project every day so when I receive the Safety AI reports, I’m able to reach out to the project team so we can discuss the activities that are in progress and determine what we need to do to get any safety risks taken care of,” he said. Safety AI automatically analyzes thousands of images already captured on construction projects, to detect all visible OSHA safety risks.

The watermark was resistant to some tampering, such as cropping text and light editing or rewriting, but it was less reliable when AI-generated text had been rewritten or translated from one language into another. It is also less reliable in responses to prompts asking for factual information, such as the capital city of France. This is because there are fewer opportunities to adjust the likelihood of the next possible word in a sentence without changing facts. However, while hallucinations represent errors from AI systems, there’s an equally concerning issue related to AI’s deliberate use to manipulate information, also known as deepfakes.

An example of synthetic data use is Google’s AlphaGo, which achieved superhuman abilities by playing against itself and learning from it. By automating routine tasks and leveraging AI-driven customer insights, agents can handle a larger client base. AI can enhance the accuracy of risk assessment and improve fraud detection processes. By analyzing vast amounts of data, AI can identify suspicious activities or inconsistencies that would otherwise go unnoticed. This helps insurers minimize fraud-related losses and allows agents to better protect their clients from potential risks.

The solution stitches together datasets captured with 3D laser scanning, mobile mapping and drones and securely shares it for more effective collaboration, Trimble said in a news release. The service is available as an extension to Trimble Connect, the firm’s cloud-based data platform that has supported more than 30 million users to date. Companies that run troll farms also use data mining and large data sets obtained from users to predict and influence voters. One famous example is Cambridge Analytica, the data analytics firm that worked with Donald Trump’s election team and the winning Brexit campaign.

OpenAI’s CEO Sam Altman Reveals That There Will Be No GPT-5 In 2024, As The Company Will Be Focusing On GPT-o1 Instead

“It’s really good, like materially better,” said one CEO who recently saw a version of GPT-5. OpenAI demonstrated the new model with use cases and data unique to his company, the CEO said. He said the company also alluded to other as-yet-unreleased capabilities of the model, including the ability to call AI agents being developed by OpenAI to perform tasks autonomously. GPT-4 is still one of the best large language models out there, and it powers Microsoft Copilot and ChatGPT Plus. However, according to Business Insider, we may see GPT-5 arrive as soon as this summer.

This simplification in AI development is set to accelerate the democratisation of AI. One of the biggest changes we might see with GPT-5 over previous versions is a shift in focus from chatbot to agent. This would allow the AI model to assign tasks to sub-models or connect to different services and perform real-world actions on its own. If it is the latter and we get a major new AI model it will be a significant moment in artificial intelligence as Altman has previously declared it will be “significantly better” than its predecessor and will take people by surprise. We should also expect to see these models—while still unreliable—become substantially more reliable than previous versions.

This article delves into what Project Strawberry is, its potential implications, and whether it signals the arrival of GPT-5. Altman likened the current state of AI technology to the early days of the iPhone, suggesting that while today’s models are useful, they are still in the nascent stages of their potential. He pointed out that current AI models, including GPT-5, are relatively small compared to what future advancements might bring.

However, based on the company’s past release schedule, we can make an educated guess. Whether it’s managing thousands of customer queries at once or providing real-time support in a busy online classroom, ChatGPT-5’s enhanced efficiency will be a significant boon. Here are a couple of features you might expect from this next-generation conversational AI. ChatGPT-5 is definitely coming with several groundbreaking features and enhancements that could level up how we interact with AI.

Tom’s Hardware is part of Future US Inc, an international media group and leading digital publisher. Aaron Klotz is a contributing writer for Tom’s Hardware, covering news related to computer hardware such as CPUs, and graphics cards. As we await official announcements from OpenAI, it’s clear that the future of conversational AI holds great promise. ChatGPT 5 could revolutionize various industries, offering new possibilities that were once thought to be science fiction. In healthcare, ChatGPT 5 will definitely improve patient interactions, provide accurate medical information, assist with research, and streamline documentation processes. It would also enhance telemedicine services and support healthcare professionals.

OpenAI is preparing to unveil GPT-5, the next generation of its large language model, in the next few months, according to leaks in a report from BI. GPT-5 is on track for summer release and has already been demonstrated to some of OpenAI’s enterprise customers. Scott also addressed the need to improve the “fragility” of AI reasoning. what is gpt 5 Current AI systems struggle with complex math problems, often requiring assistance from other systems. “Reasoning, I think, gets a lot better,” Scott said, comparing current models like the GPT-4 to high schoolers passing their AP exams. However, the next generation of AIs could pass advanced exams, such as Ph.D. qualifications.

Other questions in the Reddit AMA revealed that OpenAI indeed has its hands full. Many other answers to questions revolved around features the company is actively working on for ChatGPT. OpenAI CEO Sam Altman confirmed in a recent Reddit AMA that the next iteration of ChatGPT will not debut this year.

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It provides users with a second window in which users can transform Claude’s output into a visual project. The visual project can take different forms, such as an architecture diagram for developers or a campaign dashboard for marketers. Moreover, the upcoming ChatGPT model might be even better at researching the web for you.

Sam Altman further shared his intentions to open up the “Not Safe For Work” (NSFW) adult content sometime in the future and let users experience interactions with AI like adults without limitations. However, given the challenges such an implementation could pose, it is still a future consideration. During a Reddit AMA held this week, OpenAI’s CEO Sam Altman revealed the company’s plans for this year, and a surprising revelation also emerged. Sam Altman’s sentiments on GPT-5 being a significant leap forward were echoed by a top executive at the company, who stated today’s ChatGPT will be laughably bad within the next 12 months.

For clarity, multimodality is the ability of an AI model to process more than just text but also other types of inputs like images, audio, and video. Multimodality will be an important advancement benchmark for the GPT family of models going forward. The long-delayed GPT-5 may be significantly postponed, but it is expected to have a significant leap in performance, reaching “PhD level” intelligence. Davis explained that his repeated “calling” of models is what some of the smartest, yet smallest models on the market have done in their training process. But right now, this method is only effective for certain kinds of queries — essentially questions with an answer that is easier to check than generate.

Will GPT-5 be AGI?

However, Altman has the perspective of someone who knows what’s coming next. GPT-4 “kind of sucks” eompared to how much better he thinks the new LLM will be. Altman also addressed the company’s approach to open-source technology and the importance of democratizing AI. On the point of growing ambition, before these assistants, I would have thought about writing as good a speech as possible. By using GPT-4-quality systems, my expectations of myself have changed as well. Knowing I have access to these tools expands my willingness to use them.

However enterprise customers and app developers might pay more to access the best possible ChatGPT chatbot OpenAI can offer. But even without leaks, it’s enough to look at what Google is doing to realize OpenAI must be working on a response. Even the likes of Samsung’s chip division expect next-gen models like GPT-5 to launch soon, and they’re trying to estimate the requirements of next-gen chatbots. There’s been a lot of talk lately that the major GPT-5 upgrade, or whatever OpenAI ends up calling it, is coming to ChatGPT soon.

Microsoft CTO Kevin Scott shared this exciting development at a Berggruen Salon event in Los Angeles earlier this week. When I do, I might easily run up much larger numbers, with deep extended queries that sometimes break the context window of Claude 3 (around 150,000 words or so). I’ve started to use agentic workflows in Wordware (where I am an investor) to sometimes automate several LLMs to help with a research or analysis task. Should the current access-blocking trend continue, the research group Epoch AI predicts that developers will run out of data to train generative AI models between 2026 and 2032.

• OpenAI’s safety work also includes comprehensive internal governance and collaboration with the federal government, reinforced by regular testing, red-teaming, and board-level oversight from the company’s Safety & Security Committee.
• It could be used to enhance email security by enabling users to recognise potential data security breaches or phishing attempts.
• The goal is to help IT professionals get acquainted with new innovative products and services, but also to offer in-depth information to help them understand products and services better.
• OpenAI wants to combine multiple LLMs in time to create a bigger model that might become the artificial general intelligence (AGI) product all AI companies want to develop.

These updates “had a much stronger response than we expected,” Altman told Bill Gates in January. Individuals and organizations will hopefully be able to better personalize the AI tool to improve how it performs for specific tasks. ChatGPT (and AI tools in general) have generated significant controversy for their potential implications for customer privacy and corporate safety. Additionally, Business Insider published a report about the release of GPT-5 around the same time as Altman’s interview with Lex Fridman. Sources told Business Insider that GPT-5 would be released during the summer of 2024.

You can foun additiona information about ai customer service and artificial intelligence and NLP. “The new funding will allow us to double down on our leadership in frontier AI research, increase compute capacity, and continue building tools that help people solve hard problems.” “We are fundamentally changing how humans can collaborate with ChatGPT since it launched two years ago,” Canvas research lead Karina Nguyen wrote in a post on X (formerly Twitter). She describes it as “a new interface for working with ChatGPT on writing and coding projects that go beyond simple chat.” GPT-4 debuted on March 14, 2023, which came just four months after GPT-3.5 launched alongside ChatGPT.

One area where ChatGPT is being challenged by its rivals is in AI that can perform tasks autonomously. When asked if ChatGPT will be able to perform tasks on its own, Altman replied “IMHO this is going to be a big theme in 2025”, which indicates the direction OpenAI will be taking next year. In a recent Reddit AMA (ask me anything), ChatGPT App OpenAI CEO Sam Altman, along with some other top OpenAI executives, dropped a number of hints about the company’s future, and what to expect from ChatGPT next year. Arthur has been a tech journalist ever since 2013, having written for multiple sites. He really got into tech when he got his first tablet, the Archos 5, back in 2011.

That project now goes by the name of “Strawberry,” and according to speculation, it would be an AI model with superintelligence. The project is said to be almost finalized, and pressure from competitor Claude will make delaying the launch irresponsible. On June 7th 2023, Altman admitted to the Economic Times that “We have a lot of work to do before GPT 5. We are not certainly close to it,” adding that it is unclear even to himself what “the timeline of the next GPT” will be. Since that statement, it’s become clearer that we can expect GPT-5 to begin roll out in 2024, with a possible release date confirmation in December 2023.

Claude 3.5 Sonnet’s current lead in the benchmark performance race could soon evaporate. OpenAI CEO Sam Altman and several other company executives hosted an ask-me-anything (AMA) session on Thursday. During the session, Altman said that GPT-5 will not be released this year, however, the company plans to introduce “some very good releases” before the end of 2024. OpenAI, the trailblazing AI company behind ChatGPT, is reportedly gearing up to introduce its latest large language model (LLM), internally called Orion. Widely expected to debut as GPT-5, the new model could be a major leap towards artificial general intelligence (AGI). It will be able to perform tasks in languages other than English and will have a larger context window than Llama 2.

That’s especially true now that Google has announced its Gemini language model, the larger variants of which can match GPT-4. In response, OpenAI released a revised GPT-4o model that offers multimodal capabilities and an impressive voice conversation mode. While it’s good news that the model is also rolling out to free ChatGPT users, ChatGPT it’s not the big upgrade we’ve been waiting for. Sam Altman is not content with the current state of artificial intelligence (AI) as mere digital assistants. While ChatGPT was revolutionary on its launch a few years ago, it’s now just one of several powerful AI tools and has a lot of rivals that can perform just as well.

OpenAI is still apparently training GPT-5

In a recent interview with AI researcher Lex Fridman, ltman unpacked current state of artificial intelligence technology and the red-hot AI industry. Each new generation of models is exponentially more complicated than the previous one. They require an order of magnitude more computing operations, meaning many more chips and power. The supply of chips, data centres, power, and financial capital could be a bottleneck for the most advanced frontier models in the 4-5-year period. So I reckon a ‘generation’ is more likely to look like Schmidt’s four years.

In a recent podcast with Lex Fridman, OpenAI CEO Sam Altman said that the company will release “an amazing new model” this year. He didn’t state that it was GPT-5, but it certainly corroborates the Business Insider report that GPT-5 is likely coming this year. It’s possible that it could be called GPT-4.5 or something different, but the writing is on the wall for it to be GPT 5, especially given recent comments from Altman in the same podcast where he said that “GPT-4 kind of sucks.” Of course, the sources in the report could be mistaken, and GPT-5 could launch later for reasons aside from testing. So, consider this a strong rumor, but this is the first time we’ve seen a potential release date for GPT-5 from a reputable source.

• The New York Times indicates that the cost of housing and running OpenAI’s LLM has started to sour the relationship between OpenAI and Microsoft.
• A freelance writer from Essex, UK, Lloyd Coombes began writing for Tom’s Guide in 2024 having worked on TechRadar, iMore, Live Science and more.
• Now that it’s been over a year a half since GPT-4’s release, buzz around a next-gen model has never been stronger.
• Stuff like the progress of OpenAI’s research, the availability of necessary resources, and the potential impact of the COVID-19 pandemic on the company’s operations.

This is clearly problematic for Microsoft, as OpenAI’s GPT technology is at the heart of Microsoft’s Copilot AI software platform. PCMag.com is a leading authority on technology, delivering lab-based, independent reviews of the latest products and services. Our expert industry analysis and practical solutions help you make better buying decisions and get more from technology.

Last year, Shane Legg, Google DeepMind’s co-founder and chief AGI scientist, told Time Magazine that he estimates there to be a 50% chance that AGI will be developed by 2028. Dario Amodei, co-founder and CEO of Anthropic, is even more bullish, claiming last August that “human-level” AI could arrive in the next two to three years. For his part, OpenAI CEO Sam Altman argues that AGI could be achieved within the next half-decade. According to the report from The Verge, Orion won’t actually release as a part of ChatGPT.