The AI race just got even hotter! 🔥 Samsung has entered the arena with GAUSS, and Amazon is stepping up with its powerful new model OLYMPUS 🧠⚡. These cutting-edge AI systems are being called direct challengers to OpenAI’s ChatGPT, promising smarter conversations, deeper integrations, and massive ecosystem power 🏗️💬. From phones to smart homes to cloud computing, GAUSS and OLYMPUS could reshape the future of how we interact with AI across devices 📱🏠💻. The AI Revolution is no longer a one-horse race — it’s a full-on tech showdown! 🥊🌍
#SamsungGAUSS #AmazonOLYMPUS #ChatGPTRivals #AIRevolution #NextGenAI #TechGiantsInAI #ArtificialIntelligence #FutureTech #AIShowdown #SmartDevices #VoiceAI #MachineLearning #AmazonAI #SamsungAI #NewAIModels #GAUSSvsOLYMPUS #AICompetition #CloudAI #BigTechBattle #AIInnovation #NextBigThing
#SamsungGAUSS #AmazonOLYMPUS #ChatGPTRivals #AIRevolution #NextGenAI #TechGiantsInAI #ArtificialIntelligence #FutureTech #AIShowdown #SmartDevices #VoiceAI #MachineLearning #AmazonAI #SamsungAI #NewAIModels #GAUSSvsOLYMPUS #AICompetition #CloudAI #BigTechBattle #AIInnovation #NextBigThing
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00:00We're going to delve into three of the latest AI models that are turning heads in the tech
00:04community. First up, we'll explore Samsung's Gauss, an AI triad that's mastering language,
00:10code, and even image generation. Then we'll shift our focus to Amazon's latest titan in the AI
00:15arena, Olympus. It's a behemoth with double the parameters of GPT-4. And we can't leave out Finn's
00:21V7 model, the new kid on the block that's out to prove it's not just about size, but also about
00:26speed and precision in coding assistance. So let's get into it. Okay, Samsung has just unveiled its
00:33latest creation in the realm of AI, a language model known as Gauss. Designed as a generative
00:38pre-trained transformer, Gauss is versatile, capable of handling a slew of tasks from processing natural
00:44language to translating between languages, and even creating original text. Now, Samsung has
00:50structured Gauss into three distinct components, Gauss language, Gauss code, and Gauss image. This
00:56triad enables it to tackle tasks spanning from understanding and processing human language
01:00to generating images from textual descriptions. It's quite the multi-talented AI, adept at
01:07understanding several languages, coding in various programming languages, and bringing images to life
01:12from mere words. The real question is, how does Gauss stack up against the conversational AI titan
01:18chat GPT? Gauss is more than a sophisticated chatbot. It's a versatile AI capable of managing
01:24diverse inputs and outputs, such as text, speech, and visuals. It outpaces chat GPT with a new AI
01:31architecture that Samsung has developed, leading to enhancements in speed, accuracy, and overall
01:36intelligence. At its core, Gauss operates on what Samsung has termed the Global Unified Semantic System,
01:43or GUS. This system is a blend of deep learning, knowledge graphs, and natural language understanding,
01:49which together form an extensive model of global knowledge and phenomena. GUS is the key to Gauss's
01:55ability to assimilate new data, discern intricate patterns, and produce pertinent and cohesive
02:00responses. Plus, with on-device processing, Gauss promises a fast and secure experience without the
02:07privacy concerns that cloud-based processing might entail. Samsung's ambition for Gauss is grand.
02:13They envision it becoming an integral part of their ecosystem, starting internally with their
02:18workforce and eventually extending to consumer-facing products. They anticipate that Gauss will bolster
02:24employee efficiency in research, communication, and creative tasks. Moreover, Samsung is looking to
02:29combine Gauss with their Exynos 2400 chip, tailored for heightened AI performance and energy efficiency.
02:36The goal is to feature Gauss in future flagship products like the Galaxy S24, aiming to deliver a
02:42smooth, personalized user experience. Gauss's applications are vast and varied. It could
02:48revolutionize content creation, software development, education, and entertainment. The potential seems
02:54massive. Plus, Samsung has proactively set up an AI Red Team to scrutinize the ethical and security
02:59dimensions of their AI offerings. They're also focusing on on-device processing to maintain user privacy
03:05and provide quicker, more dependable AI services. Looking ahead, Samsung's aspirations for Gauss are to
03:12leverage the ever-evolving global knowledge base to augment user experiences. They're not just aiming
03:17for an AI model. They're aiming for an AI companion that can understand, interact, and co-create with
03:22humans, influencing the future of mobile technology and more. Now, Amazon has also stepped into the ring with
03:29an AI model called Olympus, positioned to rival the likes of OpenAI's ChatGPT and Google's Bard.
03:36Olympus is what's at the forefront of Amazon's AI endeavors, boasting a remarkable 2 trillion
03:41parameters. To put that into perspective, it's double what GPT-4 offers. This isn't just a step up.
03:47It's a leap towards a new frontier in AI technology, spearheaded by Amazon's CEO Andy Jassy.
03:53With the introduction of Olympus, Amazon is signaling its intention to become a heavyweight
03:58in the high-stakes world of AI, with potential repercussions across all their products and
04:02services. The development of Olympus is being steered by Rohit Prasad, previously at the helm of Alexa,
04:08Amazon's widely recognized voice assistant. Prasad's now leading the charge in Amazon's AI division,
04:15orchestrating their AI initiatives. The consolidation of Amazon's AI resources,
04:19with Prasad's guidance, points towards Olympus being a pivotal change agent for the company.
04:25Moreover, Amazon's $4 billion investment into AI startup Anthropic, co-founded by a former director
04:31of OpenAI, Ilya Sutskiver, suggests a heavy emphasis on scaling their AI capabilities, particularly with
04:38Olympus. Olympus is poised to transform Amazon's vast ecosystem, especially its online store and Alexa
04:44ecosystem. The integration of this AI could bring about a conversational shopping experience.
04:49Where interactions with Olympus yield tailored recommendations and efficient query resolutions.
04:55Imagine having a dialogue with Olympus and receiving personalized advice,
04:59deals, or even subscribing to premium AI features. This integration has the potential to redefine the
05:05shopping and smart home experience. Now, let's size up Olympus against ChatGPT and BARD.
05:11Olympus is said to be more capable, handling a wider array of inputs and generating more nuanced responses,
05:17all due to its extensive parameters and advanced processing. However, a larger model doesn't always
05:22mean a superior one. Experts caution that there are numerous factors at play when assessing AI
05:27performance, and larger models bring their own set of ethical, social, and ecological challenges.
05:33The unveiling of Olympus is not just about a new AI model. It's about Amazon's declaration of its
05:39commitment to AI. After the delay of their earlier AI model Titan, Amazon has regrouped with a stronger
05:45focus on Olympus, aiming to overtake OpenAI and Google. This move also reflects the industry's
05:51trajectory towards large language models as stepping stones to AGI, a goal that Amazon is well positioned
05:58to pursue with its dominance in cloud computing through AWS. Of course, Olympus does come with its share
06:05of challenges, including the technical complexities of managing such a vast model and the competitive
06:10landscape it enters into. Plus, there are the regulatory hurdles that often accompany such
06:15pioneering technology. Yet, the opportunities Olympus presents are equally compelling, potentially
06:20elevating Amazon's standing in the AI domain and paving the way for innovative products and partnerships.
06:27All right, now let's talk about another exciting development that's capturing the AI community's
06:31attention. Finn's latest AI model. What's intriguing here is that it's not merely matching the pace of
06:37the leading AI powerhouses, it's setting a new speed. Think of it as coding assistance that's been
06:43supercharged. Here's the situation. If you've worked with AI for coding, you know the struggle. There's
06:48always been this tug of war between getting your answers quickly and getting them right. GPT-4, as
06:54groundbreaking as it is, has had us tapping our fingers with its response times. For developers racing
06:59against the clock, every second counts, and waiting for an AI to churn out answers is less than ideal.
07:05Enter Finn's V7 model. It's not only on par with GPT-4's coding prowess, it's better. And when it comes
07:12to speed, we're talking about a model that's five times faster. Imagine firing off a complex question
07:18and getting a high-quality response in just 10 seconds. That's down from the 50 seconds you might
07:23expect from earlier models. So, what's under the hood of this 7th-generation AI from Finn?
07:28It's built on the back of CodeLlama34b fine-tunes, the very first models to give GPT-4 a run for its
07:35money in coding evaluations. Finn's new AI has been trained on a vast ocean of data,
07:4070 billion tokens of top-notch code and problem-solving content. And it's not just about
07:45the numbers. With a Human Evil score hitting 74.7%, it's setting new standards. But as we all know,
07:52numbers don't tell the whole story. It's real-world performance that counts,
07:56and Finn's model is proving its worth in the trenches, delivering the goods where it matters
08:01most to users. Speed is the name of the game with Finn's AI. Thanks to NVIDIA's H100S hardware
08:08and TensorRT LLM library, this model processes data at lightning speed, 100 tokens every second.
08:16But the Finn model isn't just quick, it's also deep. It can handle a massive 16,000 tokens in its
08:22responses. To put that into perspective, you can feed it inputs of up to 12,000 tokens on their
08:28website. And it still has room to include 4,000 tokens of results from the web. Now we've got to
08:34be fair, Finn's model isn't perfect. No AI is. It's still grappling with consistency, especially when
08:41the questions are complex and the answers aren't straightforward. Sometimes it might need a few
08:45more tries to nail the correct answer compared to GPT-4. But as we watch this model continue to grow
08:52we're not just spectators, we're witnessing a shift in the technological landscape. This is where AI
08:57stops being just an assistant and starts being an extension of the coder's mind.
09:02Alright, that's it for now. These new models are very exciting developments in AI and we'll be
09:07keeping a close eye on them. So stay tuned for more updates and as always, keep pushing the
09:12boundaries of tech. Thanks for watching and see you in the next one.
09:22Bye.