Gemini
How DeepSeek stacks up against ChatGPT and Gemini
In the world of conversational AI, OpenAI’s ChatGPT and Google’s Gemini have long been regarded as the frontrunners, but Chinese startup DeepSeek has made a startling entry into the race.
With its innovative and cost-efficient AI model, DeepSeek has disrupted the market, displacing ChatGPT as the App Store’s top app.
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Here’s how DeepSeek compares to its more established competitors:
Training Costs
One of DeepSeek’s most striking achievements lies in its cost-efficient training process. DeepSeek’s R1 model was trained on 10,000 NVIDIA GPUs for just $6 million — a stark contrast to the significant financial and computational resources required by OpenAI and Google. This efficiency has already made waves in the industry, with NVIDIA’s stock dropping 17% amid fears of a shift toward lower-cost AI training methods.
While ChatGPT and Gemini are renowned for their high performance, the costs of training and maintaining these models are substantially higher. This raises questions about the scalability of their approaches as demand for AI continues to grow.
Performance and Capabilities
DeepSeek’s R1 model performs competitively, delivering strong results in text coherence, factual accuracy, and specialised domain queries. However, reports suggest that it occasionally struggles with multi-step reasoning and nuanced topics where ChatGPT and Gemini excel.
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ChatGPT remains a leader in conversational flexibility and reliability, making it a popular choice for applications like customer support and content generation. Gemini, on the other hand, is highly adept at advanced reasoning and benefits from seamless integration with Google services like Search and Assistant, which enhances its utility in real-world applications.
Popularity and Market Reach
DeepSeek’s rapid rise is reflected in its download numbers. Within a week, the app reached 2.6 million downloads, securing the No. 1 spot on the US App Store and becoming a top 10 app in 111 countries overall. Its growth has been concentrated in China, the US, and Egypt, which account for most of its downloads.
In contrast, ChatGPT boasts a broader global reach, with hundreds of millions of monthly users thanks to its head start in the market and widespread integration into apps and services. Gemini, though newer, leverages Google’s vast ecosystem to quickly gain traction among users worldwide.
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Ethics and Content Moderation
A key distinction lies in how these models handle sensitive content. DeepSeek has been criticised for its pro-China bias, avoiding topics like the Tiananmen Square protests. This approach may limit its appeal in regions that value open discourse.
Meanwhile, ChatGPT and Gemini adhere to transparency and neutrality guidelines, providing balanced responses even for controversial topics. This ethical positioning enhances their credibility in markets where objectivity is a priority.
Challenges for DeepSeek
Despite its success, DeepSeek faces hurdles. Large-scale cyberattacks have disrupted access for users outside China. Its long-term viability will depend on overcoming these obstacles while continuing to innovate and expand globally.
DeepSeek’s emergence as a competitor to ChatGPT and Gemini highlights the evolving nature of the AI landscape. Its cost-effective approach and rapid market penetration demonstrate that innovation can challenge established giants. However, its ability to sustain this momentum and address concerns about ethics and global accessibility will determine whether it becomes a lasting player in the AI space.
As competition intensifies, consumers stand to benefit from improved technologies and lower costs, with DeepSeek, ChatGPT, and Gemini each pushing the boundaries of what conversational AI can achieve.
1 week ago
ChatGPT, Gemini won't reach human intelligence, Meta AI chief says
The artificial intelligence that powers systems like OpenAI's ChatGPT, Google's Gemini and Meta’s Llama will not be able to attain human levels of intelligence, said Meta's AI head Yann LeCun.
In an interview published in the Financial Times on Wednesday, he gave an insight into how the tech giant expects to develop the technology going ahead, only weeks after its plans to spend massively frightened investors and destroyed hundreds of billions from its market worth, reports Forbes.
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The models, commonly referred to as LLMs, are trained using massive quantities of data, and their capacity to properly respond to prompts is restricted by the type of the data on which they are trained, according to LeCun, implying that they are only accurate when given the appropriate training data, it said.
LLMs have a "limited understanding of logic," lack enduring memory, do not understand the physical world, and cannot plan hierarchically. LeCun said, adding that they “cannot reason in any reasonable definition of the term.”
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Because they are only accurate when fed the correct training data, LeCun, considered one of three "AI godfathers" for his fundamental contribution in the field, stated that LLMs are also "intrinsically unsafe" and that researchers seeking to produce human-level AI should look at other models, the report said.
LeCun stated that he and his roughly 500-strong team at Meta's Fundamental AI Research lab are working to develop an entirely new generation of AI systems based on an approach known as "world modelling," in which the system builds an understanding of the world around it in the same way that humans do and develops a sense of what would happen if something changed as a result, added the report.
What Is Google Gemini AI? How to Use the New Chatbot Model
LeCun predicted that human-level AI may take up to ten years to create using the world modelling technique.
8 months ago
What Is Google Gemini AI? How to Use the New Chatbot Model
The age of generative AI started its journey in 2023. Day by day, the features of generative AI like chatbots are being improved to enhance user experience around the world. Google's Bard made waves with its capabilities, but now, a new era dawns with Gemini. This innovative chatbot boasts enhanced intelligence and functionality. Join us as we explore Gemini's features, capabilities, and impact on the future of conversational AI.
What Is Google Gemini AI?
Google Gemini is the newest and most advanced artificial intelligence made by Google. It understands images, videos, text, and even sounds. What makes Gemini stand out is how it acts almost like a human. Gemini AI is good at understanding information, solving problems, and planning for the future.
Gemini has three versions: Pro, Ultra, and Nano. The Pro version has been released already, and the Ultra version will be available next year. It is expected that Gemini will play a crucial role in the latest chatbot technology, pushing the boundaries of what AI can do.
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How to Use the New Chatbot Model of Google
Gemini AI is a type of computer system called a neural network. It has been trained using a huge amount of text and code from various sources like books, articles, and code repositories. This training helps the neural network understand the patterns and connections between words and phrases in this data. As a result, Gemini AI can do things like generate text, translate languages, create different types of content, and provide informative answers to questions.
How to Use Gemini AI
If you have a Google account already, using Gemini is easy. Just go to the website using your internet browser and log in with your Google details. But remember, you need to have a Google account.
If you use a Google Workspace account, you might need to switch to your email to try Gemini.
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11 months ago
Can a bot be ‘too woke’? Google to fix Gemini’s AI image generation after criticism
Google says it will recalibrate its AI-powered art tool, after it enthusiastically embraced diversity to the point of rewriting history. Gemini bot that generates images based on text prompts, has been churning out illustrations that are as diverse as a United Nations conference, regardless of historical context. Picture this: America’s founding fathers, but not as you know them. Instead, users were surprised to find images populated with a mix of genders and ethnicities, sparking debates about accuracy versus inclusivity.
“Gemini’s AI image generation does generate a wide range of people. And that’s generally a good thing because people around the world use it. But it’s missing the mark here,” Jack Krawczyk, senior director for Gemini Experiences, was quoted by BBC.
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This isn’t the first rodeo where AI has tripped over diversity. OpenAI previously faced flak for its Dall-E generator, which seemed to cast CEOs as white men, sparking discussions on stereotypes and bias in AI.
This latest AI misadventure comes at a time when Google is eager to showcase its prowess in AI innovation. After the latest version of Gemini was released last week, critics slammed the bot for being overly politically correct, or as some have quipped, “laughably woke”.
Debarghya Das, a computer scientist, expressed frustration over Gemini’s reluctance to depict white individuals, highlighting the tool’s overcorrection. Meanwhile, author and humorist Frank J Fleming, known for his work with right-wing PJ Media, shared his disbelief when his request for a Viking image returned results that seemed to prioritize diversity over historical authenticity.
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The backlash gained traction in conservative circles, adding fuel to ongoing debates about perceived liberal biases in big tech. In response, Krawczyk emphasized Google’s commitment to representation and bias mitigation, promising adjustments to better honour historical context. “Historical contexts have more nuance to them and we will further tune to accommodate that,” he commented on X, encouraging ongoing feedback from users.
As Google navigates the tricky waters of AI, representation, and historical fidelity, the saga of Gemini’s diversity-driven missteps serves as a reminder of the complex interplay between technology, culture, and history. The tech giant’s efforts to adjust course highlight the ongoing challenge of balancing inclusivity with accuracy, a journey that continues to evolve based on user feedback and societal expectations.
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11 months ago