#largelanguagemodel

[airises]

What are the key differences between Gemini and Gemini Advanced?

Gemini and Gemini Advanced refer to different tiers of Google’s AI chatbot, distinguished primarily by model size and capabilities. Here’s a breakdown: Gemini The standard offering of Google’s conversational AI. Powered by the Pro 1.0 model. Suited for general tasks, everyday conversations, and getting quick information. Gemini Advanced The premium version of the chatbot. Leverages the…

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#AdvancedChatbot #AIresearch #AIwriting #BlogAssistant #ContentCreation #ConversationalAI #CuttingEdgeAI #Gemini #GoogleAI #GoogleInnovation #GoogleInnovationConversationalAI #InnovativeAI #LargeLanguageModel #LargeLanguageModelAIwriting #VirtualAssistant

[tagx01]

Dataset For Fine-Tuning Large Language Models

In the realm of artificial intelligence (AI), the advent of large language models (LLMs) has ushered in a new era of innovation and possibility. These monumental AI systems, built on architectures like OpenAI's GPT (Generative Pre-trained Transformer), possess an unparalleled capacity to comprehend, generate, and innovate human-like text. At the core of their remarkable capabilities lies the intricate process of fine-tuning, where these models are trained on specific datasets to tailor their performance to particular tasks or domains.

Unveiling the Power of Large Language Models:

Large language models represent the pinnacle of AI achievement, with their ability to process and understand vast amounts of textual data. Through sophisticated algorithms and deep learning techniques, these models can generate coherent text, simulate human-like conversations, and perform a myriad of natural language processing tasks with astonishing accuracy. Their potential to revolutionize industries, from healthcare to finance, is truly limitless.

Dataset For Fine-Tuning Large Language Models:

Dataset fine-tuning serves as the linchpin in optimizing the performance of large language models for specific tasks or domains. This process involves training the model on a smaller, task-specific dataset, enabling it to learn the intricacies and nuances relevant to the target task. By fine-tuning, LLMs can adapt to specialized tasks such as sentiment analysis, language translation, text summarization, and more, significantly enhancing their performance and applicability across diverse fields.

Maximizing Performance through Dataset Selection:

The success of fine-tuning hinges on the quality and relevance of the training data. Meticulous dataset selection is crucial, as it determines the model's ability to grasp the intricacies of the target task or domain. Researchers and practitioners must carefully curate datasets that encapsulate the vocabulary, patterns, and nuances essential for optimal performance. Additionally, ensuring diversity within the dataset is paramount to mitigate biases and improve the model's robustness across different contexts and demographics.

Ethical Considerations and Responsible AI:

As large language models permeate various facets of society, ethical considerations surrounding their development and deployment become paramount. Dataset curation plays a pivotal role in addressing ethical concerns, as biases or inaccuracies within training data can perpetuate societal prejudices or misinformation. By prioritizing inclusivity, diversity, and transparency in dataset selection, developers can foster the responsible and ethical use of large language models, thereby mitigating potential harms and ensuring equitable outcomes.

Future Implications and Innovations:

Looking ahead, the convergence of large language models and dataset fine-tuning holds profound implications for AI-driven innovation and advancement. From enhancing customer service through intelligent chatbots to accelerating scientific research with natural language processing, the potential applications are boundless. By harnessing the power of fine-tuning and leveraging diverse datasets, we pave the way for large language models to transcend existing boundaries and catalyze progress across myriad industries and domains.

Conclusion:

The careful selection of dataset for fine-tuning large language models is paramount for unleashing their full potential. With TagX dedication to precision in dataset curation and ethical considerations in deployment, we pave the way for AI to shape a brighter, more inclusive future.

Visit us, www.tagxdata.com

#llm #Largelanguagemodel

[outer-space-youtube]

Funny AI Bots?

The punch line is; “If Squirrels hoard Nuts like Wall-Street Traders hoard Money?”‘The AI tells it better—well, better than that one line.’Squirrels hoard Nuts to survive the winter. Humans hoard Money to be better entertained.‘That is the difference between Humans and every other animal of Planet Earth.??Don’t get mad at my shortsightedness?‘I know people are starving while food is being thrown…

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#ai #artificialintelligence #chatgpt #DataScience #DeepLearning #Largelanguagemodel #LLM #MachineLearning #NeuralNetworks #robotics #@dylan_curious #@TheAiGrid #Youtube

[phonemantra-blog]

Get ready for a revolution in AI! Google has unveiled its latest creation, the Gemini 1.5 Pro, a groundbreaking AI model boasting a significantly larger context window than its predecessor. This advancement unlocks a new level of understanding and responsiveness, paving the way for exciting possibilities in human-AI interaction. Understanding the Context Window: The Key to Smarter AI Imagine a conversation where you can reference details mentioned hours ago, or seamlessly switch between topics without losing the thread. That's the power of a large context window in AI. Essentially, the context window determines the amount of information an AI can consider at once. This information can be text, code, or even audio (as we'll see later). The larger the context window, the better the AI can understand complex relationships and nuances within the information it's processing. Google Unveils Gemini 1.5 Pro Gemini 1.5 Pro: A Quantum Leap in Contextual Understanding The standard version of Gemini 1.5 Pro boasts a massive 128,000 token window. Compared to the 32,000 token window of its predecessor, Gemini 1.0, this represents a significant leap forward. For those unfamiliar with the term "token," it can be a word, part of a word, or even a syllable. But Google doesn't stop there. A limited version of Gemini 1.5 Pro is available with an astronomical one million token window. This allows the model to process information equivalent to roughly 700,000 words, or about ten full-length books! Imagine the possibilities! This "super brain" can analyze vast amounts of data, identify subtle connections, and generate insightful responses that would be beyond the reach of traditional AI models. Beyond Context: New Features Empower Developers The impressive context window is just the tip of the iceberg. Gemini 1.5 Pro comes packed with exciting new features designed to empower developers and unlock even greater potential: Native Audio and Speech Support: Gemini 1.5 Pro can now understand and respond to spoken language. This opens doors for applications like voice search, real-time translation, and intelligent virtual assistants. Simplified File Management: The new File API streamlines how developers handle files within the model. This improves efficiency and simplifies the development process. Granular Control: System instructions and JSON mode offer developers more control over how Gemini 1.5 Pro functions. This allows them to tailor the model's behavior to specific tasks and applications. Multimodal Capabilities: The model's ability to analyze not just text but also images and videos makes it a truly versatile tool. This paves the way for innovative applications in areas like visual search, content moderation, and even autonomous vehicles. Global Accessibility: Gemini 1.5 Pro Reaches Over 180 Countries The launch of Gemini 1.5 Pro in over 180 countries, including India, marks a significant step towards democratizing AI technology. This powerful model, with its unparalleled context window and suite of new features, is no longer limited to a select few. Developers and users worldwide can now explore the potential of AI and create innovative solutions that address local and global challenges. Google's AI and Hardware Advancements: A Multi-faceted Approach Google's commitment to AI advancement extends beyond the impressive capabilities of Gemini 1.5 Pro. Here are some additional highlights from their announcement: Axion Chip Unveiled: Google has entered the ARM-based CPU market with the Axion chip. This chip promises significant improvements, boasting "up to 50% better performance and up to 60% better energy efficiency" compared to current x86-based options. This advancement could have a major impact on the efficiency and scalability of AI applications. AI Hypercomputer Gets a Boost: Google's AI Hypercomputer architecture receives an upgrade with A3 Mega VMs powered by NVIDIA H100 Tensor Core GPUs. This translates to higher performance for large-scale training and research in the field of AI. Cloud TPU v5p Now Generally Available: Cloud TPU v5p, Google's custom-designed Tensor Processing Units specifically designed for AI workloads, are now generally available. This will provide developers and researchers with easier access to the powerful processing capabilities needed for cutting-edge AI projects. FAQs Q: What is a context window in AI? A: A context window refers to the amount of information an AI model can consider at once. A larger context window allows the AI to understand complex relationships and nuances within the information it's processing. Q: How much bigger is the context window in Gemini 1.5 Pro compared to its predecessor? A: The standard version of Gemini 1.5 Pro boasts a 128,000 token window, which is four times larger than the 32,000 token window of Gemini 1.0. Q: Can Gemini 1.5 Pro understand spoken language? A: Yes, Gemini 1.5 Pro features native audio and speech support, allowing it to understand and respond to spoken language. Q: Is Gemini 1.5 Pro available in my country? A: The launch of Gemini 1.5 Pro in over 180 countries marks a significant step towards democratizing AI technology. It's likely available in your country, but you can confirm on Google's official website.

#A3MegaVMs #AIHypercomputer #AIModelCapabilities #AxionChip #ContextWindow #FileAPI #Gemini1.5Pro #GlobalAIAccessibility #googleai #GoogleUnveilsGemini1.5Pro #JSONMode #LargeLanguageModel #MultimodalCapabilities #NativeAudioSupport #SystemInstructions

[futurride]

#artificialintelligence #Cerence #CerenceChatPro #ChatGPT #Futurride #generativeAI #ID.Buzz #IDAvoiceassistant #largelanguagemodel #LLM #OpenAI #sustainablemobility #Volkswagen #VolkswagenCommercialVehicles #VW #VWBulli #VWID.BuzzGTX #VWTransporter #Wikipedia

[otiskeene]

Box Expands Its Collaboration With Microsoft With New Azure OpenAI Service Integration

Box, Inc. has recently unveiled a new partnership with Microsoft Azure OpenAI Service to introduce advanced large language models to Box AI. This collaboration enables Box customers to take advantage of cutting-edge AI models while upholding high standards for security, privacy, and compliance. The Box AI platform is now accessible to customers on Enterprise Plus plans.

Box AI is constructed on a platform-agnostic framework, allowing it to interface with robust large language models. Through the integration with Azure OpenAI Service, Box can implement sophisticated intelligence models to its Content Cloud, propelling enterprise-level AI capabilities. This joint effort is designed to assist organizations in regulated industries in harnessing AI for innovative applications.

During its beta phase, Box AI has been utilized by numerous enterprises for tasks like document analysis, content creation, and data interpretation. Wealth advisors, clinical researchers, product marketing managers, HR professionals, and nonprofit outreach specialists have all leveraged the platform to streamline operations and enhance productivity.

The integration with Microsoft 365 and Teams enhances collaboration and efficiency for mutual customers. Box users can now access and share Box content directly within Teams channels or chats, collaborate in real-time on Word, Excel, and PowerPoint files, eliminate the risks associated with email attachments, and soon integrate with Microsoft Copilot for Microsoft 365 within Teams via the Box connector for Microsoft Graph.

Read More - https://www.techdogs.com/tech-news/business-wire/box-expands-its-collaboration-with-microsoft-with-new-azure-openai-service-integration

#Box #CloudContentCollaborationSoftware #BoxAI #Microsoft365 #MicrosoftAzure #LargeLanguageModel

[govindhtech]

MediaTek Dimensity 9300 & 8300 Support Google Gemini Nano

Google Gemini Nano

An alliance between MediaTek and Google will provide powerful artificial intelligence to your smartphone using optimized dimensity chipsets. The mobile intelligence of the future is already becoming a reality, and it is occurring on devices. The Dimensity 9300 and 8300 chipsets have been optimized for use with Google Gemini Nano, which is a sophisticated large language model (LLM) meant to deliver Generative AI right to your smartphone. This partnership between MediaTek and Google was launched in late 2018. This partnership is a huge step forward, opening up fascinating possibilities for experiences driven by artificial intelligence that can be gained while on the go.

Why is the Gemini Nano so significant, and what exactly is it?

Imagine having a personal artificial intelligence assistant that is able to interpret your natural language, develop innovative text forms, and translate languages in real time, all without the need for an internet connection. Indeed, this is the promise of the Google Gemini Nano. By refining the Dimensity chipsets, Google and MediaTek are making it possible for these features to operate directly on your phone. This will result in quicker reaction times, enhanced privacy, and a decreased dependency on data use. In your opinion, what does this simply? The addition of Google Gemini Nano to your smartphone may transform it into a potent instrument for fostering creativity and enhancing productivity.

The following are some possible forms of application: Text creation on the device: With the assistance of artificial intelligence recommendations and completions, you may compose emails, poetry, scripts, or even code. The ability to communicate fluently in several languages without the need for an internet connection is made possible via real-time language translation. A voice assistant that is personalized: Your helper will provide you with replies that are more intelligent and aware of the situation. The production of content offline: To generate creative text forms such as poetry, code, screenplays, musical pieces, email, letters, and so on, even without an online connection, you may generate these formats.

The effectiveness of working together A prime example of the power that can be achieved via cooperation amongst industry experts is the optimization of Dimensity chipsets for Google Gemini Nano. By merging the cutting-edge computing power of MediaTek with the artificial intelligence skills of Google, the two businesses are pushing the frontiers of what is possible on mobile devices. In addition to providing customers with cutting-edge functionality, this alliance opens the path for a future in which artificial intelligence will be integrated into mobile devices as the standard. What comes after this? precisely as a consequence of the standardization of the Dimensity 9300 and 8300 chipsets that you could expect the arrival of smart phones that have been built with these devices in a short time. Because of this, app developers now have the possibility to build cutting-edge apps that are driven by intelligent algorithms and that take use of the powers of Gemini Nano right on your cell phone or tablet. There will be a bright future ahead for mobile intelligence, and it is unfolding now at this very moment.

Chipsets from MediaTek, the Dimensity 9300 and 8300, have been optimized for use with the Google Gemini Nano

At the end of the previous year, prior to made the announcement of the MediaTek Dimensity 9300 and 8300 SoCs, you underlined how important it was to offer third-party developers and original equipment manufacturers with the technology that would allow them to provide essential Generative AI capabilities to end users on their devices. You also brought attention to the role that these flagship and premium chipsets are playing in making that happen. These chipsets include Artificial Processing Units (APUs) that are more powerful and MediaTek’s NeuroPilot AI platform.

Gemini nano google

Google’s Large Language Model (LLM) for smartphone Generative AI

MediaTek and Google have collaborated in order to successfully integrate and optimize Google Gemini Nano, which is Google’s Large Language Model (LLM) designed to bring on-device Generative AI to smartphones. This was done in order to ensure that Gemini Nano can operate effectively and efficiently on the MediaTek Dimensity 9300 and 8300 chipsets. This is part of our ongoing investment in creating ecosystems that are necessary to ensure a strong future for artificial intelligence. For the purpose of enhancing performance, this endeavor involves working along with Google to make use of MediaTek’s NeuroPilot toolbox and porting Google Gemini Nano to MediaTek Antenna Processing Unit. When compared to cloud computing, on-device (or edge) generative artificial intelligence offers a number of benefits to both cloud computing consumers and developers. The ability to operate in locations with little to no connection, smooth performance, more privacy, improved security and dependability, reduced latency, and cheaper operating costs are some of the benefits. Other advantages include the ability to work in areas with decreased connectivity.

Google gemini nano app

As a means of assisting developers and original equipment manufacturers in the deployment of Gemini Nano apps, MediaTek and Google intend to provide an application package (APK) that is compatible with Dimensity 9300 and 8300.

Read more on Govindhtech.com

#MediaTekDimensity9300 #MediaTekDimensity8300 #GoogleGeminiNano #MediaTek #Google #GenerativeAI #largelanguagemodel #smartphone #Gemini Nano #technews #technology #govindhtech

[sifytech]

All You Need to Know about Gemini, Google's Response to ChatGPT

As Google releases its new generative AI model called Gemini, Adarsh takes you through everything we know about it so far. Read More. https://www.sify.com/ai-analytics/all-you-need-to-know-about-gemini-googles-response-to-chatgpt/

#ChatGPT #AI #ArtificialIntelligence #Deepmind #AImodel #LargeLanguageModel #LLM #GoogleBard #GoogleGemini #AlphaGo

[bricehammack]

#LargeLanguageModel

#NewYorkCity

#Manhattan

#RolfsGermanRestaurant

@rolfsny

#GermanRestaurant

#BriceDailyPhoto

#LargeLanguageModel #NewYorkCity #Manhattan #RolfsGermanRestaurant #@rolfsny #GermanRestaurant #BriceDailyPhoto

[jjbizconsult]

GPT3 who? Google's Gemini AI just dropped & it's BLOWING MINDS! (Is it the future?)

#LargeLanguageModel #LLM #AIRevolution #MachineLearning #NLProcessing #TechnologyNews #BigTech #AIUpdate #AIInnovation #FutureOfAI #GoogleBrains #GPT3Killer #TextGeneration #AIResearch #TechTalk #DeepLearning #TechTok #TechieLife #AIArt #AICreativity

[remoteresource]

Why Writers + Generative AI Large Language Model (LLM) Tools >>> Writers or AI, alone? 

#GenerativeAI #LargeLanguageModel #HireAIAssistedWriters #remoteresource #remotework #smbs #remotehiring #supportsmallbusinesses #outsourcing #smallmediumbusinesses

[thxnews]

Revolutionizing UK Defence: Google Cloud's Breakthroughs

  Unveiling the Partnership

In a groundbreaking move this June, the Defence Science and Technology Laboratory (Dstl) and Google Cloud joined forces, signing a memorandum of understanding (MOU) to propel the secure and responsible integration of artificial intelligence (AI) within the UK defence sector. The collaboration aimed to usher in a new era of technological advancement, with a specific focus on fostering the adoption of Large Language Models (LLMs).  

Powering the Future: Large Language Model Hackathon

As a tangible step toward realizing this commitment, Dstl and Google Cloud orchestrated a Large Language Model (LLM) hackathon. Executed on behalf of the Ministry of Defence's (MOD) Defence AI Centre (DAIC), the event unfolded at Google Next, attracting global attention for its role in shaping the future of AI in defence and security.   Unraveling Opportunities and Risks Gathering over 200 participants, the hackathon brought together minds from various sectors, including representatives from the Royal Navy, British Army, Royal Air Force, Space Command, MOD policymakers, ethicists, and user researchers. Facilitated by Google Cloud AI engineers, the collaborative effort aimed to harness Google's cutting-edge generative AI tools to strengthen the foundations of UK defence, security, and prosperity.   Nurturing Innovation: Prototypes for the Future Amidst intense collaboration over two days, 20 teams worked tirelessly to develop innovative, ethical, and user-centered prototypes. Aligned with the MOU's goals, these prototypes added to the growing pipeline of AI innovation ideas. The judging panel, consisting of senior HM government leaders and technology executives from Google, evaluated the prototypes across six categories, emphasizing alignment with MOD’s ethical principles for AI and Google AI Principles.   Award-Winning Breakthroughs The winning prototypes spanned diverse applications, from LLM-scanning of cybersecurity threats to LLM-enabled image analysis and data-driven predictive maintenance. The ideas birthed during the hackathon are now under consideration for further development and testing, with the ultimate goal of reaching a level of readiness where the UK Armed Forces can safely integrate them into their operations.  

Leaders Reflect on the Hackathon

Andy Bell, Dstl CTO said: “Dstl and Google Cloud brought together a hugely diverse range of participants on behalf of the MOD’s newly established DAIC, to learn, experiment and solve real-world defence problems with innovative AI technologies. This hackathon has demonstrated how creative problem-solving can be harnessed to address pressing defence challenges, paving the way for breakthroughs in generative AI for defence applications.”   John Abel, Technical Director for Google Cloud said: “This hackathon is the first step in delivering on the recent MOU signed between Dstl and Google Cloud, building on clear synergies between the 2 organisations. “The hackathon served as a powerful example of how collaboration can drive innovation and ultimately benefit the wider AI ecosystem. It also provided valuable educational and training opportunities, helping to foster the next generation of AI leaders in defence.”   Sources: THX News & Defence Science and Technology Laboratory. Read the full article

#BreakthroughsinDefenceApplications #DefenceAICentre #EthicalAIPrototypes #GenerativeAITools #GoogleCloudAI #LargeLanguageModel #MODTechnologyCollaboration #Next-GenAILeaders #UKArmedForcesIntegration #UKDefenceInnovation

[moremedtech]

ChatGPT scores nearly 50% on board certification practice ophthalmology test

ChatGPT scores nearly 50% on board certification practice ophthalmology test. A study of ChatGPT found the artificial intelligence tool answered less than half of the test questions correctly from a study resource commonly used by physicians when preparing for board certification in ophthalmology. The study, published in JAMA Ophthalmology and led by St. Michael’s Hospital, a site of Unity Health Toronto, found ChatGPT correctly answered 46 percent of questions when initially conducted in Jan. 2023. When researchers conducted the same test one month later, ChatGPT scored more than 10 percent higher. The potential of AI in medicine and exam preparation has garnered excitement since ChatGPT became publicly available in Nov. 2022. It’s also raising concern for the potential of incorrect information and cheating in academia. ChatGPT is free, available to anyone with an internet connection, and works in a conversational manner. “ChatGPT may have an increasing role in medical education and clinical practice over time, however it is important to stress the responsible use of such AI systems,” said Dr. Rajeev H. Muni, principal investigator of the study and a researcher at the Li Ka Shing Knowledge Institute at St. Michael’s. “ChatGPT as used in this investigation did not answer sufficient multiple choice questions correctly for it to provide substantial assistance in preparing for board certification at this time.” Researchers used a dataset of practice multiple choice questions from the free trial of OphthoQuestions, a common resource for board certification exam preparation. To ensure ChatGPT’s responses were not influenced by concurrent conversations, entries or conversations with ChatGPT were cleared prior to inputting each question and a new ChatGPT account was used. Questions that used images and videos were not included because ChatGPT only accepts text input. Of 125 text-based multiple-choice questions, ChatGPT answered 58 (46 percent) questions correctly when the study was first conducted in Jan. 2023. Researchers repeated the analysis on ChatGPT in Feb. 2023, and the performance improved to 58 percent. “ChatGPT is an artificial intelligence system that has tremendous promise in medical education. Though it provided incorrect answers to board certification questions in ophthalmology about half the time, we anticipate that ChatGPT’s body of knowledge will rapidly evolve,” said Dr. Marko Popovic, a co-author of the study and a resident physician in the Department of Ophthalmology and Vision Sciences at the University of Toronto. ChatGPT closely matched how trainees answer questions and selected the same multiple-choice response as the most common answer provided by ophthalmology trainees 44 percent of the time. ChatGPT selected the multiple-choice response that was least popular among ophthalmology trainees 11 percent of the time, second least popular 18 percent of the time, and second most popular 22 percent of the time. ChatGPT closely matched how trainees answer questions and selected the same multiple-choice response as the most common answer provided by ophthalmology trainees 44 percent of the time. ChatGPT selected the multiple-choice response that was least popular among ophthalmology trainees 11 percent of the time, second least popular 18 percent of the time, and second most popular 22 percent of the time. said Andrew Mihalache, lead author of the study and undergraduate student at Western University. Source: St. Michael's Hospital Read the full article

#ai #Chatgpt #largelanguagemodel #medtech #medtechnews #opthamology

[phonemantra-blog]

Google's recent announcement regarding the inclusion of Gemini Nano in the next Pixel Feature Drop has sparked excitement among Pixel 8 users. Let's delve into the details of this game-changing update and what it means for Pixel enthusiasts. A Pleasant Surprise for Pixel 8 Users Reversal of Decision: Initially, Pixel 8 users were disappointed by Google's indication that Gemini Nano wouldn't be available for their device. However, the tech giant has now reversed its decision, much to the delight of users. This turnaround follows a surge in excitement from users and developers who experienced Gemini Nano on the Pixel 8 Pro. Google Pixel 8 Embraces Gemini Nano Broader Accessibility: Google's decision to make Gemini Nano available for both Pixel 8 and Pixel 8 Pro users reflects its commitment to gathering valuable feedback from a wider audience. By enabling developers and enthusiasts to explore the capabilities of Gemini Nano, Google aims to enhance its development based on user insights. Understanding Gemini Nano: A Game-Changer in LLM Technology Scaled-Down Innovation: Gemini Nano represents a significant advancement in large language model (LLM) technology. Unlike its larger counterparts designed for data centers, Gemini Nano is a scaled-down version that operates directly on smartphones like the Pixel 8 and 8 Pro. This innovation enables powerful features such as automatic summarization and smart reply suggestions without the need for an internet connection. Offline Versatility: With Gemini Nano, users can leverage on-device AI to enjoy features like summarizing recorded conversations and receiving intelligent reply suggestions, even in offline scenarios. This capability enhances the versatility of Pixel 8 devices and elevates the overall user experience. The Impact on Pixel 8 Users Expanding Possibilities: The inclusion of Gemini Nano in the next Pixel Feature Drop marks a significant win for Pixel 8 users. It opens up a broader range of features and functionalities, empowering users to make the most of their devices. Additionally, the exploration of Gemini Nano's capabilities by developers and enthusiasts is expected to drive further advancements in the Pixel ecosystem. FAQs Q: What is Gemini Nano? A: Gemini Nano is a scaled-down version of a large language model (LLM) designed to operate directly on smartphones, offering features like automatic summarization and smart reply suggestions. Q: How does Gemini Nano benefit Pixel 8 users? A: Pixel 8 users can leverage on-device AI with Gemini Nano to enjoy features such as summarizing recorded conversations and receiving intelligent reply suggestions, even without an internet connection. Q: Why is Google making Gemini Nano available for Pixel 8 users? A: Google aims to gather valuable feedback from a wider audience of developers and enthusiasts to enhance the development of Gemini Nano and drive further advancements in the Pixel ecosystem. Q: When will Gemini Nano be available for Pixel 8 users? A: Gemini Nano is expected to be included in the next Pixel Feature Drop, with Google following its traditional launch timeline. Keep an eye out for updates from Google regarding the release date. Q: Can Pixel 8 users expect more features with Gemini Nano in the future? A: Yes, the broader exploration of Gemini Nano's capabilities by developers and enthusiasts is likely to lead to further advancements and additional features for Pixel 8 users in future updates.

#GeminiNano #googlepixel8 #GooglePixel8EmbracesGeminiNano #Googleupdates #LargeLanguageModel #LLMtechnology #ondeviceAI #Pixel8Pro #PixelFeatureDrop #Pixelusers #SmartReply #smartphonetechnology #summarization

[futurride]

#AmazonAlexa #AR #augmentedreality #automatedparking #BMW #BMWConnectedDriveStore #BMWMotorrad #BMWOperatingSystem9 #CES #CES2024 #DTSAutoStage #Futurride #gaming #generativeAI #in-carvideostreaming #infotainment #IntelligentPersonalAssistant #largelanguagemodel #LLM #MetaRealityLabs #Mini #mixedreality #MR #sustainablemobility #TiVo #Valeo #Xperi #Xreal #XrealAir2

[l-l-m]

Memo of reading OPEN AI document_01_230307

Temperature param makes the outcoming result with more diversity.

#LLM #GPT #ChatGPT #AI #artificialintelligence #UltraIntelligence #UltraGODs #machinelarning #Superintelligence #LargeLanguageModel