Google has officially launched GEMINI — its most powerful AI model yet! 💥📡 Capable of multimodal reasoning, coding, and creative tasks, Gemini is set to challenge GPT and redefine the AI landscape 🌐⚙️. Are we witnessing the future of artificial intelligence unfold before our eyes? 🔮💡
00:00Alright, so here's the big news. Google has finally released Gemini, the AI model everyone's been waiting for since GPT-4 came out.
00:07And it was a total surprise. In this video, we'll look at the technical aspects, what Gemini is capable of, and how it stacks up against GPT-4.
00:16So let's get into it.
00:17Alright, so Gemini is Google's new AI, a super smart tool that understands text, images, sounds, videos, and more, all at once.
00:25Launched on December 6, 2023, it's part of Google's big push into AI, making it a key feature in their products.
00:32There are three versions of Gemini, Nano for personal use, Pro for professional work, and Ultra for advanced research.
00:39These run on Google's special Tensor Processing Units, TPUs, that make AI tasks efficient and cost-effective.
00:47Gemini is challenging OpenAI's GPT-4, boasting higher efficiency and versatility by outperforming it in multiple areas.
00:54This AI model stands out because it can work with different types of data like text, images, sounds, videos, and code all at the same time.
01:03This makes it super versatile in solving complex tasks.
01:07Now, Gemini Ultra is the most powerful version of Gemini, and it is designed for training and fine-tuning large and complex deep learning models that feature many matrix calculations, such as building large language models.
01:18It has achieved human expert-level performance on the MMLU exam benchmark, which is a test that covers 57 tasks, including elementary mathematics, U.S. history, computer science, law, and more.
01:32Gemini Ultra scored 86.5% on average, while GPT-4 scored 70%.
01:38Gemini Ultra also excels at multimodal reasoning tasks, such as answering questions based on images, videos, or graphs, or generating summaries or reviews based on multimodal inputs.
01:49Gemini Pro and Nano are the smaller and cheaper versions of Gemini, and they are designed for specific applications and use cases.
01:57Gemini Pro is ideal for a variety of use cases, such as chatbots, code generation, media content generation, synthetic speech, vision services, recommendation engines, personalization models, among others.
02:10Gemini Nano is ideal for personal and small-scale use, such as education, entertainment, gaming, hobby, and social media.
02:17Both of these smaller models can leverage the pre-trained models from Gemini Ultra or fine-tune them for their own purposes.
02:24Now let's see how Gemini performs compared to GPT-4 on different benchmarks and tasks.
02:30One of the most widely used and comprehensive benchmarks for natural language understanding is SuperGLUE, which stands for General Language Understanding Evaluation.
02:39It's a tough test that checks how well an AI can understand language by making it do things like reading and answering questions.
02:46Gemini Ultra got a score of 92.3 here, beating GPT-4's 89.8.
02:50This means Gemini did better at reading and understanding stuff in 6 out of 8 tests.
02:56Then there's MMFusion, which is about how good the AI is at handling different types of data, like text, pictures, and videos.
03:03Gemini Ultra scored 81.7 here, which is better than GPT-4's 76.4.
03:09This shows Gemini is really good at working with a mix of information, like answering questions about a picture or a video.
03:15We also have Alpha Code 2, a coding challenge.
03:18It's about writing, fixing, and improving computer code.
03:21Out of 100 coding tasks, Gemini Ultra scored 94.6, higher than GPT-4's 88.2.
03:29It actually outperformed GPT-4 on 82 out of 100 coding tasks and tied with GPT-4 on the remaining 18.
03:36Gemini showed a significant advantage over GPT-4 in tasks that involve writing and running code in Python, Java, and C++,
03:45as well as in tasks that involve using advanced programming concepts, such as recursion, loops, functions, and classes.
03:52It also showed a slight edge over GPT-4 in tasks that involve writing and running code in HTML, CSS, and JavaScript,
03:59as well as in tasks that involve using basic programming concepts such as variables, operators, and conditionals.
04:06But now when we talk about integration of the model, it is actually designed to make Google's products like Google Search, Google Workspace, and Google Bard better.
04:15Like it helps Google Search give better answers and summaries, and it makes Google Workspace tools, like Help Me Write and Smart Canvas, more productive and creative.
04:24Also, Gemini is useful for Google Cloud, offering advanced AI features for things like recognizing speech and language or writing code.
04:32It's making Google Bard more engaging by giving more natural responses and working with different languages.
04:38For Google's devices, like Pixel and Nest, Gemini adds features like voice control and recognizing faces and objects.
04:45It's the same for Google Ads, Google's tool for online advertising.
04:48Right now, it uses AI to make and improve ads based on what the advertiser wants.
04:53But Gemini is going to take this to the next level by adding things like audio and video to the ads.
04:58All right, now Gemini is built on a transformer model, which is a type of neural network that's really good at understanding relationships between words and sentences.
05:07For training, it uses self-supervised learning, which means it learns from large amounts of data without needing humans to label it.
05:14This type of learning is great because it can use the data itself to get better.
05:17And it complements supervised learning, where data is labeled and more specific.
05:21Gemini's training uses big data sets like conceptual captions, audio set, YouTube 8M, and GitHub.
05:27And it has different goals, like understanding masked language or images, aligning different types of data, or generating one type of data from another.
05:35It actually uses various techniques to make the model smaller and faster without losing quality.
05:40This includes quantization, which reduces the precision of numbers in the model, and pruning, which gets rid of parts that aren't really needed.
05:47There's also distillation, where a big, complex model teaches a smaller, simpler one, and the sparsification, which makes the model less dense.
05:55Google's Tensor Processing Units, or TPUs, also help make Gemini more efficient.
06:00These are specialized AI accelerators designed to be faster and more energy efficient than general-purpose processors.
06:07Google's massive infrastructure, including data centers and networks, also plays a big part in supporting Gemini.
06:13Now, since this new AI model is really powerful, it comes with big responsibilities.
06:18It can impact society and the environment in huge ways.
06:21And there's a chance it could cause problems like bias, misinformation, and privacy issues.
06:26So it's really important that Gemini is used in a way that's good for everyone.
06:30Google makes sure of this by using their Responsible AI Framework.
06:34This framework guides them in making Gemini fair, private, secure, safe, accountable, environmentally friendly, and beneficial for society.
06:43For fairness, Google works to ensure Gemini treats everyone equally and doesn't discriminate, especially against those who are already disadvantaged.
06:51When it comes to privacy, Google protects personal information using techniques like encryption.
06:57They also focus on making Gemini secure against cyberattacks and ensuring it doesn't harm people physically or mentally.
07:03Accountability is a big deal, too.
07:06Google wants to be clear about how Gemini works and be responsible for its outcomes.
07:10They do things like audits and reports to stay transparent.
07:14And for the planet, they try to minimize Gemini's environmental impact, making it as eco-friendly as possible.
07:20Lastly, they want Gemini to contribute to society positively, like supporting health and education.
07:25So there you have it.
07:27Gemini is a pretty big deal in the AI world, and it looks like it's doing better than GPT-4 on paper and in tests.
07:33But what do you think?
07:34Will Gemini be better than GPT-4 in real life, too?
07:37Drop your thoughts in the comments.
07:39And if you're into AI and tech stuff, don't forget to hit the like and subscribe button.
07:43Thanks for tuning in, and I'll catch you in the next video.
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