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 A recent video post by Akash James of SparkCognition shows how he was able to get the GPU he needed to work on his multi-modal LLM called VERsatile ONline Intelligent Cognitive Agent (VERONICA) by accessing compute he owned in India from the Himalayas. Join the Z by HP Boost webinar Oct 4th @ 9 am PST to hear how Akash is accessing his GPU remotely to create AI. 

I am looking to run some testing on a local ollama model in AI Studio. However, every time I open AI Studio, I have to redownload ollama and pull llama3 to use from my notebook. Any suggestion for how to save that download (done from terminal) so that it is already loaded when I open AI Studio?

I'm a Researcher, We want to work on Artificial intelligence, Deep learning and Machine Learning algorithms on healthcare databases. We have a budget of about 30,00,000/- Lakhs Indian rupees to spend. Please suggest a Workstation and an NVIDIA GPU under this budget. 

HP & NVIDIA AI Influencer Event at NVIDIA GTC 2025When: March 19, 2025 | 7:30 PM – 9:30 PM PDTWhere: Loft Bar & Bistro - Dining Room, San Jose, CAEngage with top AI influencers Discuss cutting-edge AI trends Expand your industry connectionsSecure your spot! https://register.nvidia.com/flow/nvidia/gtcs25/se73345/form/rsvp

 AI is evolving fast, and with all the hype, it’s easy to lose sight of what really matters. In a recent conversation, Thomas H. Davenport and Randy Bean broke down five key AI trends that will shape the year ahead—helping leaders cut through the noise and focus on what’s actually changing the game.n this discussion, they cover:Agentic AI: Hype vs. Reality – How to navigate the excitement and actual impact. AI ROI Matters – Why businesses need to track real value, not just trends. Data-Driven Culture Struggles – The persistent roadblocks to making data central to decision-making. Unstructured Data Challenges – Why tackling messy data is more important than ever. Evolving AI Leadership – How roles and reporting structures are shifting in the AI era.Drawing from

Imagine teaching a robot to boil water. It might first search for a pot, fill it with water, then place it on the stove. But what if it mistakenly turns on the microwave instead of the stove? Traditional AI agents often struggle to recover from such errors, leading to cascading failures. This is the problem Agent-R—a novel framework for training self-reflective language model agents—aims to solve.In this article, we’ll unpack the theoretical backbone of Agent-R by focusing on how this framework redefines error recovery in AI.Why Error Recovery Matters in Interactive EnvironmentsMost AI agents learn by mimicking expert trajectories (e.g., perfect step-by-step guides). But real-world tasks are messy. Errors are inevitable, and waiting until the end of a task to correct them is like letting a typo i

Multi-agent systems have become increasingly important in solving complex problems through distributed intelligence and collaboration. However, coordinating multiple agents effectively remains a significant challenge, particularly in the field of reinforcement learning. In this article, we'll explore a novel approach called Shared Recurrent Memory Transformer (SRMT) that aims to enhance coordination in decentralized multi-agent systems.The Challenge of Multi-Agent CoordinationImagine a group of robots trying to navigate through a crowded warehouse. Each robot has its own goal and can only see what's immediately around it. How can they work together efficiently without bumping into each other or getting stuck? This is the essence of the multi-agent pathfinding problem.Traditional approaches often struggle with this task, especially when the environment is complex or the number of agents is large. They may rely on centralized control, which doesn'

 A research paper by Ali Behrouz, Peilin Zhong and Vahab Mirrokni from Google Research introduce a groundbreaking neural network module that addresses the limitations of current models in handling long term dependencies. This work is a significant leap forward in the design of memory augmented architectures, offering theoretical and practical advancements in sequence modeling. Below we explore the theoretical underpinnings, technical innovations and experimental results of this advanced neural network module.The Challenge of Long-Term DependenciesModern neural architectures like Transformers and recurrent neural networks (RNNs) have revolutionized sequence modeling. However, they face some challenges:Transformers: While effective at capturing short term dependencies through atte

 Image generated using CopilotArtificial intelligence (AI) systems are becoming increasingly sophisticated, capable of generalizing across tasks and domains. However, this complexity makes them harder to understand, raising concerns about their trustworthiness and safety. Mechanistic interpretability offers a promising solution by reverse-engineering neural networks to uncover how they process information internally. Just as neuroscience advanced our understanding of the brain by studying internal cognitive processes, mechanistic interpretability seeks to move beyond black-box methods to provide precise, causal explanations of AI behavior.This article explores the principles, methods, and implications of mechanisti

Google announced its Willow project with amazing claims on performance capabilities. 

We’re excited to recognize Ayon Roy as our latest Z by HP Ambassador of the Month! 🎉As an Executive Data Scientist at NielsenIQ, Ayon is making waves in sustainable innovation with his project, Greenscape AI. This AI-powered framework for urban forestry is reshaping how cities approach sustainability. By integrating satellite imagery and drone footage, Greenscape AI maps tree species, analyzes spatial distributions, and creates high-resolution urban forestry maps. These tools help optimize urban green space management, contribute to climate action, and promote ecosystem preservation.Ayon credits the ZBook Studio G10 and

Really great article from Anthropic with the announcement of MCPhttps://www.anthropic.com/news/model-context-protocolAnthropic has unveiled an exciting new initiative: the Model Context Protocol (MCP). This open-source standard simplifies the connection between AI assistants and various data sources, making integration seamless for developers. MCP includes developer tools, local server support within Claude Desktop applications, and pre-configured servers for popular platforms like Google Drive and GitHub. Notably, companies such as Block and Apollo are already leveraging MCP to enhance their AI capabilities.A standout feature of MCP is its remarkable flexibility; it is designed to connect with data sources that may not even exist yet. Developers can easily get started with quickstart guides and open-sou

With the proliferation of chatbots and agents, users are rushing to learn more about the technology. The speed with which GenAI is growing is fueled by the data with which the AI has access to. Chatbots are curating a combination of synthetic and user based content to collect questions, data, chain of thought, and context.Do you believe sharing your data and logic online with AI means giving up rights to your IP?  

 The rapid evolution of Large Language Models (LLMs) has ushered in a new era of AI-powered chat assistants, leveraging techniques like supervised instruction fine-tuning and reinforcement learning with human feedback (RLHF) to enhance their instruction-following and conversational abilities. These advancements have led to models that are increasingly aligned with human preferences, often outperforming their unaligned predecessors in user satisfaction. However, this progress has brought forth a significant challenge: how to effectively evaluate these sophisticated models. Traditional benchmarks, which typically focus on core capabilities such as knowledge retrieval and problem-solving, fall short in assessing how well these models align with human preferences in real-world applications. We've observed instances where models excel in benchmark te

 Hello Community Members!October has been an eventful month, filled with engaging activities, insightful news, and exciting events. Let's take a look back at the highlights, dive into our latest webinar recap, and learn how you can contribute your ideas to Boost and AI Studio initiatives. Here’s your October community recap!🎤 Last Webinar RecapZ by HP Boost Webinar On October 4th, we hosted a highly informative webinar focused on maximizing on-premise compute power for AI and ML model training. Akash James demonstrated how he leverages remote GPU access from the Himalayas to work on his multi-modal LLM project, VERONICA. His presentation not only highlighted innovative techniques but also inspired many attendees to explore remote compute solutions for their own AI

Gartner projects that AI-powered PCs will hit 114 million units in 2025, marking a massive 165.5% jump from 2024. These AI PCs, defined by their built-in neural processing units (NPUs), include models running on Windows, macOS, and Arm-based systems.By 2024, shipments are expected to reach 43 million units, nearly double the 2023 total. Laptops lead the way, with AI-enabled models predicted to make up 51% of all laptop shipments by 2025, outpacing desktops.Gartner forecasts AI PC shipments to reach 43 million units in 2024, a 99.8% increase from 2023.AI PC Shipments, Worldwide, 2023-2025 (Thousands of Units)     2023 Shipments

Stanford University research team explores gain cell memory technology to address the limitations of current SRAM and DRAM memory in GPUs. By combining features of both SRAM and DRAM, the goal is to speed up data access and reduce power consumption.Top Three Takeaways:Gain Cell Memory: hybrid gain cells combine the speed of SRAM with the capacity of DRAM, to overcome the memory wall problem in GPUs by reducing data transfer delays. Innovative Materials: combining different materials for transistors (ALD ITO FET and Si PMOS), the hybrid gain cells provide faster data access, non-destructive reads, and significantly longer data retention compared than traditional DRAM. Potential for SoC Applications: can serve as a drop-in replacement for SRAM, offering higher capacity at lower fabrication costs, making it attractive for SoC manufacturers in datacenter GPUs,

As we wrap up September 2024, we're thrilled to spotlight standout stories, articles, and posts from our vibrant community.  Celebrating Our Z by HP Ambassador of the Month: Javier Eluney Hernández 🎉 We were thrilled to honor Javier Eluney Hernández as our very first ever Z by HP Ambassador of the Month. Javier has significantly advanced AI research, particularly in Computer Vision and Generative AI applications within healthcare.With a sustained passion for exploring the frontiers of machine learning, Javier's work spans computer

With the wrap-up of HP Imagine yesterday, AI and remote work took center stage in every new product announcement. One key highlight was the introduction of Z by HP Boost, a solution that enables teams to share on-demand GPU power from their combined fleet of local workstations. Additionally, HP is expanding AI Studio to strengthening LLM development with a “built-in layer of trust” by protecting against hallucinations and bias.HP also announced several exciting AI-powered PC, audio, and visual products, including the new HyperX Cloud MIX™ 2 headset, Poly Labs, and the HP OmniBook Ultra Flip 2-in-1 Laptop Next Gen AI PC