adaptAI Inc.

?? Small Language Models (SLMs): The Future of Efficient AI Agents ??? SLMs have been around for over a year now, and we've been exploring their capabilities at adaptAI for several months. The results? They’re simpler to work with and require significantly fewer resources compared to traditional large models. ?? What Makes SLMs So Special? Low resource usage: Run on thinly provisioned VMs or even laptops! ?? Cost-effective: With fewer parameters, they generate less computational noise, which translates to lower TCO (Total Cost of Ownership) over time. ?? Faster deployment: SLMs are much quicker and easier to deploy, making them ideal for simple, service-oriented AI agents. ?? SLMs & RAG: A Powerful Pair When it comes to retrieval-augmented generation (RAG), incorporating vectorized data into an SLM is just as efficient as using larger models—but with a huge boost in efficiency and reduced resource demands. The use case is key: Simple AI agents that need to answer concise questions—think HR policies, travel procedures, or internal queries. ???? ?? Focus on Simplicity, Not Complexity SLMs shine when you need a straightforward, concise response. The ability to control things like the temperature parameter ensures that answers stay brief and to the point. ?? Lifecycle Management While SLMs can be a breeze to deploy, managing their lifecycle can be tricky, so we wouldn't recommend this architecture just yet for large-scale deployments. ??? But the journey is just beginning… and it's getting easier, faster, and more efficient every day! ?? ?? Key Takeaway: If you're building an agentic solution with simple, actionable AI—SLMs may be exactly what you need. Just keep in mind: the business use case should always drive your choice of model. ?? ?? Ready to explore how SLMs can help you save resources and improve efficiency? Let’s chat! ?? #AI #SmallLanguageModels #MachineLearning #Efficiency #CostSavings #AdaptAI #AIUseCases #TechInnovation #RAG #BusinessSolutions

?? Join Us Today at the South Florida Manufacturing Association Annual Gala! We’re excited to be part of this year’s South Florida Manufacturing Association Annual Gala! ?? What’s in store? We'll be showcasing cutting-edge autonomous service robots in collaboration with our amazing partner ToDo Robotics LLC. ?? Where to find us? Visit us at Booth #36 to see the future of robotics in action. ??? We can’t wait to connect with fellow industry professionals and discuss how these robots are revolutionizing manufacturing and service industries! See you there! ?? #Innovation #Robotics #Manufacturing #Automation #Tech #SouthFloridaGala #TodoRobotics #FutureOfWork #TodoRobotics #Robots #AI

adaptAI is now officially on TikTok! Follow us there for funny and brief snippets about our work. At adaptAI, we make it easy and simple to work with LLMs. https://lnkd.in/eCnqa2_7

This partnership significantly boosts the model's efficiency for real-time applications and makes AI deployments more scalable and cost-effective. Loving Llama 3.2B Models ?? #adaptAi

Recent news indicates a growing interest among companies in developing private Large Language Models (LLMs) due to the high costs associated with public models and infrastructure. - Cost and Infrastructure Concerns: Companies are increasingly considering private LLMs as a cost-effective solution to manage the high expenses of public models like OpenAI's GPT series. Private LLMs offer predictable pricing and allow organizations to leverage existing infrastructure, reducing the need for expensive hardware upgrades. - Data Security and Privacy: Private LLMs provide enhanced data security and privacy, crucial for industries with strict regulatory requirements. By hosting their own models, companies can ensure compliance with standards like GDPR and HIPAA, and protect sensitive data from external exposure. - Customization and Control: Organizations benefit from the ability to customize and fine-tune private LLMs to meet specific needs, offering greater control over the model's performance and integration with existing systems. This customization is often not possible with third-party models. - Strategic Decisions: Businesses face a strategic choice between building proprietary LLMs or adopting pre-built solutions. Developing in-house capabilities can offer long-term competitive advantages and cost efficiencies, despite the initial investment required. Sources The Case for Private LLMs in Organizations - SearchBlox https://lnkd.in/eChibfZX LLM Hosting (Private Language Models) - adaptAI https://lnkd.in/eCzw2N2b How to build enterprise-grade proprietary LLMs? - LeewayHertz https://lnkd.in/eYpW54WU The LLM Dilemma: Choosing Between Building or Buying https://lnkd.in/emAcQ_3N Cost-Effective LLMs: Leveraging Generative AI with Limited Hardware https://lnkd.in/eNXpfDn5 Reducing Costs in LLM Architectures - Top Techniques - DagsHub https://lnkd.in/euSK8YKp Full LLM Power 40% Cheaper: Model Cascade Mixture of Thought ... https://lnkd.in/erU-XhcM LLM Implementation Cost Breakdown - LinkedIn https://lnkd.in/eFK6Qi6G

OpenAI continues to be pressured by the market to raise its monthly subscription, that coupled with the real concern that most production AI Agents are built over this one single-point-of-failure makes adaptAI's Private LLM offer that much more attractive. Why placed all your bets on one platform? https://lnkd.in/dk2BGAWp

Yesterday adaptAI Inc. experienced an unexpected outage which caused a bit of confusion. We immediately went into panic mode!? Who doesn’t? But then, I remembered that we had developed an AI Agent that scans certain key log files (tail -f $numrecs) and feeds it into an LLM for determination of any anomalies. ? We simply asked (or prompted) the agent: Are there any anomalies in our key daemons??And voila!?We got a root cause! This is yet another example of how Generative AI can help you be more efficient. Generative AI has the potential to completely transform how we handle unexpected outages. It’s great at sifting through huge amounts of logs, events, and performance data from different systems and apps to spot patterns or anomalies that might be easy to overlook. When it identifies a problem, it can quickly create a set of detailed troubleshooting steps, like suggestions for system checks, configuration tweaks, or software updates. This not only helps resolve issues faster but also makes sure IT professionals follow a clear and effective troubleshooting process. Learn how to take advantage of this technology, book time to speak with us now. Email us here: [email protected]

adaptAI Inc. is committed to making our AI solutions ethical and clean of any security vulnerabilities. Cyber Security experts are already taking steps to help mitigate the new risks that may be exposed through enterprise AI agents.

You don’t have to be a huge enterprise to deploy well governed AI assistants. Start with a simple idea. * Don’t wait for others’ use cases * Think of a process that causes you the most pain/work/time * Start simple: low risk high impact Get in touch with us; we will help you build an AI crew of agents that will deliver value within weeks, in your environment, with your data.

The business value of adaptAI, or similar smaller-scale language models, lies in their ability to offer advanced AI capabilities with reduced resource requirements compared to larger models like GPT-4. Here are some key points on the business value: 1. Cost Efficiency: adaptAI's models are less resource-intensive, meaning they require less computational power and storage, leading to lower operational costs for businesses deploying them. 2. Scalability: Due to their smaller size, adaptAI's models can be easily scaled and integrated into various applications, enabling businesses to deploy AI solutions across different platforms and environments without significant infrastructure changes. 3. Customization: Smaller models like adaptAI Inc.'s models can be fine-tuned more quickly and efficiently for specific business needs, allowing companies to develop tailored AI solutions that closely align with their industry or use case. 4. Faster Deployment: With reduced complexity and resource demands, adaptAI Inc.'s models can be deployed faster, enabling businesses to bring AI-powered products and services to market more quickly. 5. Accessibility: By lowering the barrier to entry, adaptAI's models democratize access to advanced AI technologies, allowing smaller companies or startups to leverage AI without needing the extensive resources typically required for larger models. 6. Privacy and Compliance: Smaller models can be more easily hosted on-premises or within specific regions, helping businesses comply with data privacy regulations by keeping sensitive information within controlled environments. 7. Agility: adaptAI's models can be more responsive and agile in real-time applications, providing faster inference times and improving the user experience in customer-facing or interactive systems. 8. Energy Efficiency: The lower energy consumption of adaptAI's models contributes to sustainability efforts, making them an environmentally friendly choice for companies looking to reduce their carbon footprint. These factors contribute to the strategic advantage for businesses leveraging adaptAI Inc.'s or similar small language models in their AI initiatives. #adaptAI