Gemini 1.5: Google’s Latest AI Challenges GPT-4 🤖🚀 | AI Showdown Begins! | AI Revolution - video Dailymotion

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Google unveils Gemini 1.5, its most advanced AI model yet — built to compete directly with OpenAI’s GPT-4 🔥🧠. With massive context windows, improved reasoning, and lightning-fast performance, Gemini 1.5 is redefining what next-gen AI can do 💡⚡. Is this the model that finally shakes OpenAI's dominance? Let the AI war begin! 🎯🤖  #Gemini15 #GoogleAI #GPT4 #OpenAI #AIRevolution #GeminiVsGPT #GenerativeAI #ArtificialIntelligence #MachineLearning #AIBattle #NextGenAI #TechNews #AIShowdown #GoogleVsOpenAI #FutureOfAI #LLM #AIUpdate #AITrends #LargeLanguageModels #GeminiAI

Transcript

00:00Google has just lifted the curtain on a brand new AI marvel, Gemini 1.5, and it's stirring up quite

00:07the buzz. In a note from Google and Alphabet CEO Sundar Pichai, we were introduced to the fruits

00:13of Google's relentless innovation, closely following the heels of its predecessor, Gemini

00:181.0 Ultra. This advancement is not just a step, but a giant leap in the realm of artificial

00:24intelligence, designed to make Google's suite of products even more useful, starting with Gemini

00:29Advanced. Now, both developers and cloud customers are invited to the party, given the green light to

00:35start tinkering with 1.0 Ultra through the Gemini API in AI Studio and Vertex AI. But hold on a second,

00:43the innovation train doesn't stop there. Google, with safety as its compass, is already rolling out

00:48the next-gen model, Gemini 1.5. This new iteration is a powerhouse, boasting improvements that span

00:55multiple dimensions. Notably, Gemini 1.5 Pro stands shoulder-to-shoulder in quality with 1.0 Ultra,

01:02yet it demands less computational power. That's no small feat. The real game-changer, however,

01:08is the model's ability to understand long contexts. Gemini 1.5 can juggle up to 1 million tokens with

01:14ease, setting a new standard for large-scale foundation models. This breakthrough is more

01:19than just a technical milestone. It opens up a world of possibilities, enabling the creation of

01:24more capable and helpful applications and models. In a detailed exposition by Demis Hassabis, CEO of

01:30Google DeepMind, we're taken deeper into the excitement surrounding Gemini 1.5. This next-generation

01:36model is not just an update, it's a transformation. Built on a new mixture of experts, MOE architecture,

01:42Gemini 1.5 is more efficient to train and serve, making it a lean, mean AI machine. Gemini 1.5 Pro,

01:50the first model rolled out for early testing, is a multimodal mid-size model. It's designed to excel

01:55across a broad spectrum of tasks, performing on par with Google's largest model to date,

02:001.0 Ultra. But the cherry on top is its experimental feature for understanding long contexts.

02:06With a standard context window of 128,000 tokens, a select group of developers and enterprise

02:12customers are getting a sneak peek at its capabilities, with a context window stretching

02:17up to 1 million tokens through AI Studio and Vertex AI in a private preview. As Google works to fully

02:24unleash the 1 million token context window, the focus is on optimizing the model to improve latency,

02:30cut down computational demands, and polish the user experience. The anticipation for developers to

02:36test this capability is palpable, with more details on its broader availability on the horizon.

02:42Gemini 1.5 stands on the shoulders of giants, drawing from Google's pioneering research in

02:47transformer and MOE architectures. Unlike traditional transformer models, which operate as a single,

02:53large neural network, MOE models are segmented into smaller, expert networks. These models dynamically

03:00activate the most relevant pathways for a given input, significantly boosting efficiency.

03:05The advancements in Gemini 1.5's architecture have turbocharged its ability to learn complex tasks

03:11swiftly, while maintaining high quality and operational efficiency. These improvements are a testament to

03:17Google's commitment to rapid iteration and delivery of more sophisticated AI models.

03:22The concept of a model's context window might sound technical, but it's essentially the amount of

03:27information the model can process at once. Think of it as the model's capacity to digest and analyze

03:33data, whether text, images, videos, audio, or code. The larger the context window, the more data the model can

03:40handle, resulting in outputs that are more consistent, relevant, and useful. Gemini 1.5,

03:47Pro's ability to process up to 1 million tokens, is nothing short of revolutionary. This capacity enables the

03:53model to tackle enormous amounts of information in one go. Whether it's an hour of video content,

03:5811 hours of audio, code bases with more than 30,000 lines, or documents exceeding 700,000 words,

04:06Gemini 1.5 Pro is up to the task. The team has even pushed the boundaries further in research,

04:12successfully testing up to 10 million tokens. The implications of this are vast.

04:17Gemini 1.5 Pro can analyze, classify, and summarize large volumes of content with ease.

04:24For instance, when presented with the extensive 402-page transcripts from Apollo 11's mission to

04:29the moon, it can sift through conversations, events, and details with remarkable precision.

04:35Moreover, Gemini 1.5 Pro excels in understanding and reasoning across different modalities,

04:41including video. Given a silent Buster Keaton movie, the model can dissect plot points and events,

04:47and notice subtleties that might escape human viewers. This capability extends to the realm

04:52of coding as well. When faced with prompts containing over 100,000 lines of code, Gemini 1.5 Pro

04:59demonstrates an uncanny ability to navigate through the examples, suggest modifications,

05:04and elucidate on the workings of different code segments. This level of proficiency in handling

05:09extensive blocks of code opens up new avenues for problem-solving and debugging, making Gemini 1.5 Pro

05:16a valuable asset for developers. The performance of Gemini 1.5 Pro is nothing short of impressive.

05:22In a series of comprehensive evaluations covering text, code, image, audio, and video,

05:28Gemini 1.5 Pro outshines 1.0 Pro in 87% of the benchmarks used to develop Google's large

05:36language models. What's more, when pitted against 1.0 Ultra on the same metrics,

05:41Gemini 1.5 Pro showcases a performance level that's broadly equivalent. One of the standout

05:47features of Gemini 1.5 Pro is its robust in-context learning capability. This means the model can pick

05:54up new skills from the information provided in a lengthy prompt without the need for additional

05:58fine-tuning. This skill was put to the test in the machine translation from one book, MTOB Benchmark,

06:05which evaluates the model's ability to learn from previously unseen information. When given a

06:10grammar manual for Calamang, a language spoken by fewer than 200 people worldwide, Gemini 1.5 Pro

06:17demonstrated the ability to translate English to Calamang with a proficiency comparable to that

06:23of a human learning from the same material. The introduction of Gemini 1.5 Pro's long context

06:28window is a pioneering step for large-scale models. As this feature is unprecedented, Google is

06:33developing new evaluations and benchmarks to assess its novel capabilities thoroughly.

06:38Alongside these technical feats, Google places a strong emphasis on ethics and safety in AI

06:44development. Adhering to its AI principles and robust safety protocols, Google ensures that its models,

06:50including Gemini 1.5 Pro, undergo rigorous ethics and safety testing. This process involves integrating

06:57research findings into governance processes, model development, and evaluations to continuously refine

07:03AI systems. Since the debut of 1.0 Ultra in December, Google has refined the model to enhance its safety for

07:10broader release. This includes conducting innovative research on potential safety risks and developing

07:15red-teaming techniques to identify and mitigate possible harms. Before launching 1.5 Pro, Google applied

07:22the same meticulous approach to responsible deployment as it did with the Gemini 1.0 models. This includes

07:29comprehensive evaluations focusing on content safety, representational harms, and the development of

07:35additional tests to accommodate the unique long-context capabilities of 1.5 Pro. Google's commitment to

07:42responsibly bringing each new generation of Gemini models to the global community is unwavering.

07:48Starting today, a limited preview of 1.5 Pro is available to developers and enterprise customers

07:53via AI Studio and Vertex AI. Further details about this initiative can be found on Google's developer

08:00and Google Cloud blogs. Looking ahead, Google plans to release 1.5 Pro with a standard 128,000 token

08:08context window, with pricing tiers that accommodate up to 1 million tokens as the model undergoes further

08:14enhancements. Early testers have the opportunity to explore the 1 million token context window at no cost

08:20during the testing period, albeit with longer latency times due to the experimental nature of

08:26this feature. However, significant improvements in processing speed are anticipated. Developers keen

08:31on experimenting with Gemini 1.5 Pro are encouraged to sign up in AI Studio, while enterprise customers can

08:38contact their Vertex AI account team for more information.

08:42Alright, that wraps up our video. If you liked it, please consider subscribing and sharing so we can

08:47keep bringing more content like this. Thanks for watching and see you in the next one.

Gemini 1.5: Google’s Latest AI Challenges GPT-4 🤖🚀 | AI Showdown Begins! | AI Revolution

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