#OpenAI ChatGPT Development Services

[mobiloittetech]

How to Integrate ChatGPT with Your Website for Enhanced User Engagement

In today's digital age, providing excellent customer support and engaging user experiences on websites is crucial for businesses. One way to enhance user interaction is by integrating ChatGPT, an AI-powered chatbot, into your website. ChatGPT can understand and respond to user queries in a conversational manner, creating a seamless and interactive experience. In this blog post, we will guide you through the process of integrating ChatGPT with your website, helping you unlock the power of AI-driven customer engagement.

1. Choose a ChatGPT Platform

There are several platforms available that provide ChatGPT services, such as OpenAI's ChatGPT API. Evaluate different platforms based on factors like pricing, ease of integration, scalability, and customization options. Select a platform that aligns with your specific requirements.

2. Obtain API Access

Sign up for the chosen ChatGPT platform and obtain API access. This typically involves creating an account, subscribing to a plan, and receiving an API key or credentials necessary for API integration.

3. Set up Server-Side Integration

To integrate ChatGPT with your website, you will need to set up server-side integration. This involves making API calls from your website's backend to the ChatGPT API. The exact implementation will depend on your server-side programming language or framework.

4. Implement User Interface

Design and implement the user interface for the chatbot on your website. This includes creating a chat widget or integrating the chatbot into existing chat or messaging systems. Customize the appearance and behavior of the chatbot to align with your website's branding and user experience.

5. Handle User Requests

When a user interacts with the chatbot on your website, capture their messages or queries and send them to the server-side code. Use the ChatGPT API to send these user messages as API requests and retrieve the responses.

6. Process Responses and Display

Once you receive the responses from the ChatGPT API, process them on the server-side code. You can handle intents, extract information, and perform any necessary business logic. Finally, send the processed response back to the user interface for display.

7. Enhance the Chatbot's Abilities

Continuously improve and enhance the capabilities of your ChatGPT integration. Experiment with different training approaches, fine-tune the chatbot's responses, and iterate based on user feedback. Regularly update and retrain the chatbot model to ensure it stays up-to-date and provides accurate and relevant responses.

8. Monitor and Evaluate Performance

Monitor the performance of your ChatGPT integration by analyzing user interactions, measuring response times, and tracking user satisfaction metrics. Collect feedback from users to identify areas for improvement and address any issues that arise.

Conclusion

Integrating ChatGPT with your website can significantly enhance user engagement and customer support. By following the steps outlined in this guide, you can seamlessly integrate ChatGPT into your website, providing users with a conversational and interactive experience. Remember to choose a reliable ChatGPT platform, set up server-side integration, implement the user interface, handle user requests, process and display responses, enhance the chatbot's abilities, and monitor its performance. With ChatGPT, you can take your website's user experience to the next level and deliver exceptional customer engagement.

[mobiloitteuk]

OpenAI ChatGPT Development by Mobiloitte UK

Introducing OpenAI ChatGPT – revolutionizing customer engagement. Harness the power of AI to enhance user interactions, drive conversions, and boost productivity. Empower your brand with Mobiloitte.uk's expertise in crafting seamless, intelligent solutions. Unleash ChatGPT's potential for a transformative digital experience – the future of innovation is now, with Mobiloitte.uk

[cizotech]

AI without good data is just hype.

Everyone’s buzzing about Gemini, GPT-4o, open-source LLMs—and yes, the models are getting better. But here’s what most people ignore:

👉 Your data is the real differentiator.

A legacy bank with decades of proprietary, customer-specific data can build AI that predicts your next move.

Meanwhile, fintechs scraping generic web data are still deploying bots that ask: "How can I help you today?"

If your AI isn’t built on tight, clean, and private data, you’re not building intelligence—you’re playing catch-up.

Own your data.

Train smarter models.

Stay ahead.

In the age of AI, your data strategy is your business strategy.

[umanologicinc]

How to Integrate ChatGPT into Your Application: A Step-by-Step Guide

In today’s digital era, artificial intelligence (AI) has become a crucial part of business solutions. One of the most impactful AI tools is ChatGPT – a powerful language model created by OpenAI that can simulate human-like conversations. Integrating ChatGPT into your application can revolutionize your business by automating customer support, enhancing user engagement, and providing personalized interactions.

This guide will walk you through the process of integrating ChatGPT into your application step by step. Whether you're an app developer, a business owner, or someone interested in AI technologies, this guide will provide the information you need to get started.

1 . Understand Your Requirements Before you dive into integrating ChatGPT, it’s essential to define the goals you want to achieve with AI in your application. Do you want to automate customer service, create virtual assistants, or enable advanced conversational interfaces? Understanding your objectives will help determine how you should use ChatGPT within your application.

If you're unsure about which AI features will benefit your business most, consulting with experts can help. Umano Logic, based in Canada, specializes in understanding client needs and offering the right ChatGPT integration solutions for your business.

2 . Understand Your Requirements

Before jumping into integrating ChatGPT, it is vital to establish the purpose you intend to fulfill with AI within your application. Do you wish to automate customer support, develop virtual assistants, or facilitate sophisticated conversational interfaces? Knowing your objectives will assist in determining how to utilize ChatGPT within your application.

If you're not sure which AI capabilities will most help your business, talking to experts can. Umano Logic, a Canadian company, is experienced at getting to know client needs and providing the appropriate ChatGPT integration solutions for your business. 3 . Set Up the API OpenAI offers a friendly API to bring ChatGPT into your program. The API provides access to strong language models and lets you customize the AI to your individual requirements.

Following is a step-by-step summary of what needs to be done:

Get your API key from OpenAI: Register on OpenAI and grab your API key.

Install libraries: Depending upon your programming language, install OpenAI client libraries.

Configure the API: Create parameters for creating AI responses from user input.

The technical implementation may look daunting, but since we have the seasoned team of Umano Logic, we can assist you with each step of the way and make sure that the integration is completely smooth and seamless.

4 . Design the User Interface

With the backend installed, the second step is designing how the users will interact with the ChatGPT. The user interface (UI) should be intuitive and user-friendly with simple, understandable options for the users to begin chatting with the AI.

Remember the following when designing the UI:

User-friendly chat window

Quick response buttons

Personalized interaction based on user input

At Umano Logic, we can assist you in creating a clean, minimal, and efficient UI that maximizes the user experience and makes using AI seamless. 5 . Train and Customize ChatGPT

Although ChatGPT comes with pre-trained models, you might want to fine-tune it for your specific business needs. You can train the model to understand your products, services, and industry-specific terminology. This ensures that users get the most relevant answers when they interact with the AI.

Customizing ChatGPT can greatly improve the quality of the interactions and make the AI feel more natural and intuitive. Umano Logic offers training and customization services to make sure the AI understands your business and communicates effectively with users.

6 . Test and Refine

Once everything is set up, it's important to test the integration thoroughly. Test the ChatGPT interactions, making sure the responses are accurate, relevant, and helpful. The feedback from users will be invaluable in refining and improving the AI system.

At Umano Logic, we offer comprehensive testing services to ensure that your ChatGPT integration works flawlessly. Our experts will help you monitor the system and make improvements to keep the AI model in top shape.

7. Monitor and Improve

After launching the integration, it’s essential to continuously monitor how the AI performs. Regular monitoring helps identify any issues early, while also providing insights into how users are interacting with ChatGPT. You can use this information to improve responses and adapt the AI to better suit your business goals.

Conclusion:

Adding ChatGPT to your application isn't a trend it's a wise step toward business modernisation and improved customer experiences. From response automation to personalised assistance, ChatGPT can enable you to serve users more professionally and efficiently. The process might look technical, but if guided correctly, it's an easy task.

At Umano Logic, we're experts at ensuring businesses everywhere in Canada can seamlessly integrate AI tools such as ChatGPT into their sites. Whether you're a new startup looking to innovate with new technology or a long-established business wanting to take your customer care to the next level, our staff is here to guide you through each stage, from planning and installation to testing and beyond.

If you're prepared to introduce AI into your app and remain ahead of the digital curve, call Umano Logic today. Let's craft intelligent, beneficial, and forward-thinking solutions collectively.

Visit Now to learn more about ChatGPT Integration

visit:: https://www.umanologic.ca/chatgpt-integration-service-edmonton

[atcuality3]

Designing the Future with Human-Centered AI Solutions - Atcuality

Atcuality creates technology that understands people. Our approach blends empathy-driven design with technical excellence to build intuitive systems that resonate with users and transform operations. We believe that great digital products start with a deep understanding of human behavior and business objectives. Our work spans industries, from healthcare and finance to logistics and education—each project shaped by purpose and guided by data. In the heart of our solutions is a proprietary AI powered application architecture that adapts to user behavior, improves outcomes, and scales intelligently. By integrating AI with custom development, we provide smarter experiences that grow more valuable over time. Whether you're launching a new service or reimagining legacy software, Atcuality delivers intelligent systems designed for the way people live, work, and connect today.

[zxdfgh]

[annajamessa]

Finding a reputed generative AI development company is challenging in this competitive environment. Here is an Inforgraphic unveiling the Top Generative hashtag#AI development companies in 2024. To Know More visit:- https://www.antiersolutions.com/top-10-generative-ai-development-companies-to-look-out-for-in-2024/

[nitor-infotech]

How does ChatGPT work?

Imagine having a conversation with a chatbot that feels almost human. That’s exactly what OpenAI ChatGPT brings to the table. The remarkable technology of Generative Pre-trained Transformer (GPT) powers it.

ChatGPT utilizes Natural Language Processing (NLP) techniques. These help it to learn from past conversations and generate response options.

It is trained on massive amounts of human interaction data. This results in an AI that can understand and have conversations like humans. It was released as a free research preview/prototype in November 2022. It is powered by a machine learning model called GPT-3, developed by OpenAI.

Click here to read more-

[maimajane]

Top Chatbot Development Services company in India

Zethic is one of the top AI chatbot Development Companies in India and offers top-notch custom chatbot development solutions that redefine innovation and ensure client satisfaction across. Our team of experts strives for excellence in AI chatbot app development services in India, leveraging the latest technologies and best practices. Our commitment to quality, timeliness, and affordability has earned us a reputation as a reliable partner for businesses seeking to elevate their digital presence and experience excellence in AI chatbot development in India with Zethic.

[probablyasocialecologist]

An increasing number of Silicon Valley investors and Wall Street analysts are starting to ring the alarm bells over the countless billions of dollars being invested in AI, an overconfidence they warn could result in a massive bubble. As the Washington Post reports, investment bankers are singing a dramatically different tune than last year, a period marked by tremendous hype surrounding AI, and are instead starting to become wary of Big Tech's ability to actually turn the tech into a profitable business. "Despite its expensive price tag, the technology is nowhere near where it needs to be in order to be useful," Goldman Sach's most senior stock analyst Jim Covello wrote in a report last month. "Overbuilding things the world doesn’t have use for, or is not ready for, typically ends badly."

[...]

According to Barclays analysts, investors are expected to pour $60 billion a year into developing AI models, enough to develop 12,000 products roughly the size of OpenAI's ChatGPT. But whether the world needs 12,000 ChatGPT chatbots remains dubious at best. "We do expect lots of new services... but probably not 12,000 of them," Barclays analysts wrote in a note, as quoted by the WaPo. "We sense that Wall Street is growing increasingly skeptical." For quite some time now, experts have voiced concerns over a growing AI bubble, comparing it to the dot-com crisis of the late 1990s. "Capital continues to pour into the AI sector with very little attention being paid to company fundamentals," tech stock analyst Richard Windsor wrote in a March research note, "in a sure sign that when the music stops there will not be many chairs available." "This is precisely what happened with the Internet in 1999, autonomous driving in 2017, and now generative AI in 2024," he added.

27 July 2024

[umanologicinc]

How to Integrate ChatGPT into Your Application: A Step-by-Step Guide

In today’s digital era, artificial intelligence (AI) has become a crucial part of business solutions. One of the most impactful AI tools is ChatGPT – a powerful language model created by OpenAI that can simulate human-like conversations. Integrating ChatGPT into your application can revolutionize your business by automating customer support, enhancing user engagement, and providing personalized interactions.

Visit: https://www.umanologic.ca/chatgpt-integration-service-edmonton

[mariacallous]

On Saturday, an Associated Press investigation revealed that OpenAI's Whisper transcription tool creates fabricated text in medical and business settings despite warnings against such use. The AP interviewed more than 12 software engineers, developers, and researchers who found the model regularly invents text that speakers never said, a phenomenon often called a “confabulation” or “hallucination” in the AI field.

Upon its release in 2022, OpenAI claimed that Whisper approached “human level robustness” in audio transcription accuracy. However, a University of Michigan researcher told the AP that Whisper created false text in 80 percent of public meeting transcripts examined. Another developer, unnamed in the AP report, claimed to have found invented content in almost all of his 26,000 test transcriptions.

The fabrications pose particular risks in health care settings. Despite OpenAI’s warnings against using Whisper for “high-risk domains,” over 30,000 medical workers now use Whisper-based tools to transcribe patient visits, according to the AP report. The Mankato Clinic in Minnesota and Children’s Hospital Los Angeles are among 40 health systems using a Whisper-powered AI copilot service from medical tech company Nabla that is fine-tuned on medical terminology.

Nabla acknowledges that Whisper can confabulate, but it also reportedly erases original audio recordings “for data safety reasons.” This could cause additional issues, since doctors cannot verify accuracy against the source material. And deaf patients may be highly impacted by mistaken transcripts since they would have no way to know if medical transcript audio is accurate or not.

The potential problems with Whisper extend beyond health care. Researchers from Cornell University and the University of Virginia studied thousands of audio samples and found Whisper adding nonexistent violent content and racial commentary to neutral speech. They found that 1 percent of samples included “entire hallucinated phrases or sentences which did not exist in any form in the underlying audio” and that 38 percent of those included “explicit harms such as perpetuating violence, making up inaccurate associations, or implying false authority.”

In one case from the study cited by AP, when a speaker described “two other girls and one lady,” Whisper added fictional text specifying that they “were Black.” In another, the audio said, “He, the boy, was going to, I’m not sure exactly, take the umbrella.” Whisper transcribed it to, “He took a big piece of a cross, a teeny, small piece … I’m sure he didn’t have a terror knife so he killed a number of people.”

An OpenAI spokesperson told the AP that the company appreciates the researchers’ findings and that it actively studies how to reduce fabrications and incorporates feedback in updates to the model.

Why Whisper Confabulates

The key to Whisper’s unsuitability in high-risk domains comes from its propensity to sometimes confabulate, or plausibly make up, inaccurate outputs. The AP report says, "Researchers aren’t certain why Whisper and similar tools hallucinate," but that isn't true. We know exactly why Transformer-based AI models like Whisper behave this way.

Whisper is based on technology that is designed to predict the next most likely token (chunk of data) that should appear after a sequence of tokens provided by a user. In the case of ChatGPT, the input tokens come in the form of a text prompt. In the case of Whisper, the input is tokenized audio data.

The transcription output from Whisper is a prediction of what is most likely, not what is most accurate. Accuracy in Transformer-based outputs is typically proportional to the presence of relevant accurate data in the training dataset, but it is never guaranteed. If there is ever a case where there isn't enough contextual information in its neural network for Whisper to make an accurate prediction about how to transcribe a particular segment of audio, the model will fall back on what it “knows” about the relationships between sounds and words it has learned from its training data.

According to OpenAI in 2022, Whisper learned those statistical relationships from “680,000 hours of multilingual and multitask supervised data collected from the web.” But we now know a little more about the source. Given Whisper's well-known tendency to produce certain outputs like "thank you for watching," "like and subscribe," or "drop a comment in the section below" when provided silent or garbled inputs, it's likely that OpenAI trained Whisper on thousands of hours of captioned audio scraped from YouTube videos. (The researchers needed audio paired with existing captions to train the model.)

There's also a phenomenon called “overfitting” in AI models where information (in this case, text found in audio transcriptions) encountered more frequently in the training data is more likely to be reproduced in an output. In cases where Whisper encounters poor-quality audio in medical notes, the AI model will produce what its neural network predicts is the most likely output, even if it is incorrect. And the most likely output for any given YouTube video, since so many people say it, is “thanks for watching.”

In other cases, Whisper seems to draw on the context of the conversation to fill in what should come next, which can lead to problems because its training data could include racist commentary or inaccurate medical information. For example, if many examples of training data featured speakers saying the phrase “crimes by Black criminals,” when Whisper encounters a “crimes by [garbled audio] criminals” audio sample, it will be more likely to fill in the transcription with “Black."

In the original Whisper model card, OpenAI researchers wrote about this very phenomenon: "Because the models are trained in a weakly supervised manner using large-scale noisy data, the predictions may include texts that are not actually spoken in the audio input (i.e. hallucination). We hypothesize that this happens because, given their general knowledge of language, the models combine trying to predict the next word in audio with trying to transcribe the audio itself."

So in that sense, Whisper "knows" something about the content of what is being said and keeps track of the context of the conversation, which can lead to issues like the one where Whisper identified two women as being Black even though that information was not contained in the original audio. Theoretically, this erroneous scenario could be reduced by using a second AI model trained to pick out areas of confusing audio where the Whisper model is likely to confabulate and flag the transcript in that location, so a human could manually check those instances for accuracy later.

Clearly, OpenAI's advice not to use Whisper in high-risk domains, such as critical medical records, was a good one. But health care companies are constantly driven by a need to decrease costs by using seemingly "good enough" AI tools—as we've seen with Epic Systems using GPT-4 for medical records and UnitedHealth using a flawed AI model for insurance decisions. It's entirely possible that people are already suffering negative outcomes due to AI mistakes, and fixing them will likely involve some sort of regulation and certification of AI tools used in the medical field.

[justforbooks]

The Optimist by Keach Hagey

The man who brought us ChatGPT. Sam Altman’s extraordinary career – and personal life – under the microscope

On 30 November 2022, OpenAI CEO Sam Altman tweeted the following, characteristically reserving the use of capital letters for his product’s name: “today we launched ChatGPT. try talking with it here: chat.openai.com”. In a reply to himself immediately below, he added: “language interfaces are going to be a big deal, i think”.

If Altman was aiming for understatement, he succeeded. ChatGPT became the fastest web service to hit 1 million users, but more than that, it fired the starting gun on the AI wars currently consuming big tech. Everything is about to change beyond recognition, we keep being told, though no one can agree on whether that will be for good or ill.

This moment is just one of many skilfully captured in Wall Street Journal reporter Keach Hagey’s biography of Altman, who, like his company, was then virtually unknown outside of the industry. He is a confounding figure throughout the book, which charts his childhood, troubled family life, his first failed startup Loopt, his time running the startup incubator Y Combinator, and the founding of OpenAI.

Altman, short, slight, Jewish and gay, appears not to fit the typical mould of the tech bro. He is known for writing long, earnest essays about the future of humankind, and his reputation was as more of an arch-networker and money-raiser than an introverted coder in a hoodie.

OpenAI, too, was supposed to be different from other tech giants: it was set up as a not-for-profit, committed by its charter to work collaboratively to create AI for humanity’s benefit, and made its code publicly available. Altman would own no shares in it.

He could commit to this, as he said in interviews, because he was already rich – his net worth is said to be around $1.5bn (£1.13bn) – as a result of his previous investments. It was also made possible because of his hyper-connectedness: as Hagey tells it, Altman met his software engineer husband Oliver Mulherin in the hot tub of PayPal and Palantir co-founder Peter Thiel at 3am, when Altman, 29, was already a CEO, and Mulherin was a 21-year-old student.

Thiel was a significant mentor to Altman, but not nearly so central to the story of OpenAI as another notorious Silicon Valley figure – Elon Musk. The Tesla and SpaceX owner was an initial co-founder and major donor to the not-for-profit version of OpenAI, even supplying its office space in its early years.

That relationship has soured into mutual antipathy – Musk is both suing OpenAI and offering (somewhat insincerely) to buy it – as Altman radically altered the company’s course. First, its commitment to releasing code publicly was ditched. Then, struggling to raise funds, it launched a for-profit subsidiary. Soon, both its staff and board worried the vision of AI for humanity was being lost amid a rush to create widely used and lucrative products.

This leads to the book’s most dramatic sections, describing how OpenAI’s not-for-profit board attempted an audacious ousting of Altman as CEO, only for more than 700 of the company’s 770 engineers to threaten to resign if he was not reinstated. Within five days, Altman was back, more powerful than ever.

OpenAI has been toying with becoming a purely private company. And Altman turns out to be less of an anomaly in Silicon Valley than he once seemed. Like its other titans, he seems to be prepping for a potential doomsday scenario, with ranch land and remote properties. He is set to take stock in OpenAI after all. He even appears to share Peter Thiel’s supposed interest in the potential for transfusions of young blood to slow down ageing.

The Optimist serves to remind us that however unprecedented the consequences of AI models might be, the story of their development is a profoundly human one. Altman is the great enigma at its core, seemingly acting with the best of intentions, but also regularly accused of being a skilled and devious manipulator.

For students of the lives of big tech’s other founders, a puzzling question remains: in a world of 8 billion human beings, why do the stories of the people wreaking such huge change in our world end up sounding so eerily alike?

Daily inspiration. Discover more photos at Just for Books…?

[manorinthewoods]

"Welcome to the AI trough of disillusionment"

"When the chief executive of a large tech firm based in San Francisco shares a drink with the bosses of his Fortune 500 clients, he often hears a similar message. “They’re frustrated and disappointed. They say: ‘I don’t know why it’s taking so long. I’ve spent money on this. It’s not happening’”.

"For many companies, excitement over the promise of generative artificial intelligence (AI) has given way to vexation over the difficulty of making productive use of the technology. According to S&P Global, a data provider, the share of companies abandoning most of their generative-AI pilot projects has risen to 42%, up from 17% last year. The boss of Klarna, a Swedish buy-now, pay-later provider, recently admitted that he went too far in using the technology to slash customer-service jobs, and is now rehiring humans for the roles."

"Consumers, for their part, continue to enthusiastically embrace generative AI. [Really?] Sam Altman, the boss of OpenAI, recently said that its ChatGPT bot was being used by some 800m people a week, twice as many as in February. Some already regularly turn to the technology at work. Yet generative AI’s ["]transformative potential["] will be realised only if a broad swathe of companies systematically embed it into their products and operations. Faced with sluggish progress, many bosses are sliding into the “trough of disillusionment”, says John Lovelock of Gartner, referring to the stage in the consultancy’s famed “hype cycle” that comes after the euphoria generated by a new technology.

"This poses a problem for the so-called hyperscalers—Alphabet, Amazon, Microsoft and Meta—that are still pouring vast sums into building the infrastructure underpinning AI. According to Pierre Ferragu of New Street Research, their combined capital expenditures are on course to rise from 12% of revenues a decade ago to 28% this year. Will they be able to generate healthy enough returns to justify the splurge? [I'd guess not.]

"Companies are struggling to make use of generative AI for many reasons. Their data troves are often siloed and trapped in archaic it systems. Many experience difficulties hiring the technical talent needed. And however much potential they see in the technology, bosses know they have brands to protect, which means minimising the risk that a bot will make a damaging mistake or expose them to privacy violations or data breaches.

"Meanwhile, the tech giants continue to preach AI’s potential. [Of course.] Their evangelism was on full display this week during the annual developer conferences of Microsoft and Alphabet’s Google. Satya Nadella and Sundar Pichai, their respective bosses, talked excitedly about a “platform shift” and the emergence of an “agentic web” populated by semi-autonomous AI agents interacting with one another on behalf of their human masters. [Jesus christ. Why? Who benefits from that? Why would anyone want that? What's the point of using the Internet if it's all just AIs pretending to be people? Goddamn billionaires.]

"The two tech bosses highlighted how AI models are getting better, faster, cheaper and more widely available. At one point Elon Musk announced to Microsoft’s crowd via video link that xAI, his AI lab, would be making its Grok models available on the tech giant’s Azure cloud service (shortly after Mr Altman, his nemesis, used the same medium to tout the benefits of OpenAI’s deep relationship with Microsoft). [Nobody wanted Microsoft to pivot to the cloud.] Messrs Nadella and Pichai both talked up a new measure—the number of tokens processed in generative-AI models—to demonstrate booming usage. [So now they're fiddling with the numbers to make them look better.

"Fuddy-duddy measures of business success, such as sales or profit, were not in focus. For now, the meagre cloud revenues Alphabet, Amazon and Microsoft are making from AI, relative to the magnitude of their investments, come mostly from AI labs and startups, some of which are bankrolled by the giants themselves.

"Still, as Mr Lovelock of Gartner argues, much of the benefit of the technology for the hyperscalers will come from applying it to their own products and operations. At its event, Google announced that it will launch a more conversational “AI mode” for its search engine, powered by its Gemini models. It says that the AI summaries that now appear alongside its search results are already used by more than 1.5bn people each month. [I'd imagine this is giving a generous definition of 'used'. The AI overviews spawn on basically every search - that doesn't mean everyone's using them. Although, probably, a lot of people are.] Google has also introduced generative AI into its ad business [so now the ads are even less appealing], to help companies create content and manage their campaigns. Meta, which does not sell cloud computing, has weaved the technology into its ad business using its open-source Llama models. Microsoft has embedded AI into its suite of workplace apps and its coding platform, Github. Amazon has applied the technology in its e-commerce business to improve product recommendations and optimise logistics. AI may also allow the tech giants to cut programming jobs. This month Microsoft laid off 6,000 workers, many of whom were reportedly software engineers. [That's going to come back to bite you. The logistics is a valid application, but not the whole 'replacing programmers with AI' bit. Better get ready for the bugs!]

"These efforts, if successful, may even encourage other companies to keep experimenting with the technology until they, too, can make it work. Troughs, after all, have two sides; next in Gartner’s cycle comes the “slope of enlightenment”, which sounds much more enjoyable. At that point, companies that have underinvested in AI may come to regret it. [I doubt it.] The cost of falling behind is already clear at Apple, which was slower than its fellow tech giants to embrace generative AI. It has flubbed the introduction of a souped-up version of its voice assistant Siri, rebuilt around the technology. The new bot is so bug-ridden its rollout has been postponed.

"Mr Lovelock’s bet is that the trough will last until the end of next year. In the meantime, the hyperscalers have work to do. Kevin Scott, Microsoft’s chief technology officer, said this week that for AI agents to live up to their promise, serious work needs to be done on memory, so that they can recall past interactions. The web also needs new protocols to help agents gain access to various data streams. [What an ominous way to phrase that.] Microsoft has now signed up to an open-source one called Model Context Protocol, launched in November by Anthropic, another AI lab, joining Amazon, Google and OpenAI.

"Many companies say that what they need most is not cleverer AI models, but more ways to make the technology useful. Mr Scott calls this the “capability overhang.” He and Anthropic’s co-founder Dario Amodei used the Microsoft conference to urge users to think big and keep the faith. [Yeah, because there's no actual proof this helps. Except in medicine and science.] “Don’t look away,” said Mr Amodei. “Don’t blink.” ■"

[dertaglichedan]

DeepSeek hit with large-scale cyberattack, says it’s limiting registrations

DeepSeek on Monday said it would temporarily limit user registrations “due to large-scale malicious attacks” on its services.

The Chinese AI startup recently toppled OpenAI’s ChatGPT from its title of most-downloaded free app in Apple’s App Store.

DeepSeek on Monday said it would temporarily limit user registrations “due to large-scale malicious attacks” on its services, though existing users will be able to log in as usual.

The Chinese artificial intelligence startup has generated a lot of buzz in recent weeks as a fast-growing rival to OpenAI’s ChatGPT, Google’s Gemini and other leading AI tools.

Earlier on Monday, DeepSeek took over rival OpenAI’s coveted spot as the most-downloaded free app in the U.S. on Apple’s App Store, dethroning ChatGPT for DeepSeek’s own AI Assistant. It helped inspire a significant sell-off in global tech stocks.

Buzz about the company, which was founded in 2023 and released its R1 model last week, has spread to tech analysts, investors and developers, who say that the hype — and ensuing fear of falling behind in the ever-changing AI hype cycle — may be warranted. Especially in the era of the generative AI arms race, where tech giants and startups alike are racing to ensure they don’t fall behind in a market predicted to top $1 trillion in revenue within a decade.

[darkmaga-returns]

It was only a matter of time before an innovative mind created the next mainstream AI tool to compete with ChatGPT. In a massive step toward AI advancement, Liang Wenfeng of China launched DeepSeek, an open-source large language models (LLM) intended to compete if not one day overshadow ChatGPT. The launch immediately wiped $1 trillion off the US stock exchange and the tech competition between China and the US is coming to a head.

ChatGPT is run by OpenAI. Its creation marked the dawn of a new way of interacting with the internet and accessing information. Users can ask AI to instantaneously perform actions and it is reshaping the way the world operated. People have created businesses based on ChatGPT. There have been countless warnings of AI replacing human jobs. Governments are still uncertain how to regulate these services and the data they pull from users. Of course, countless services like ChatGPT have launched in recent years, but DeepSeek may be the next best alternative.

Wenfeng hired all the top minds graduating from Chinese universities and paid them top dollar to create DeepSeek for a fraction of what it took to create ChatGPT. OpenAI’s GPT-4, launched in 2023, cost $100 million to develop; DeepSeek-R1 began with a $6 million investment.