Highly Autonomous Self Learning AI Agent
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The document describes a proposed highly autonomous self-learning AI agent (HASL) that uses machine learning and neural networks to remotely detect people and analyze emotions from video feeds. The system would recognize occupants using CCTV and smartphone camera feeds, understand emotions and predict actions. It would communicate with security systems and store user information like name, ID, location and emotion in a MongoDB database. The proposed system requires hardware like processors, RAM, storage and GPUs, as well as software like UIMA, ConceptNet and machine learning algorithms to perform multimodal analysis and prediction.
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Guest Speaker Segment with Hannah Barrington: Dive into the world of dynamic real estate marketing with Hannah, the Marketing Manager at Workspace Group. Hear firsthand how their team generates engaging descriptions for thousands of office units by integrating diverse data sources—from PDF floorplans to web pages—using FME transformers, like OpenAIVisionConnector and AnthropicVisionConnector. This use case will show you how GenAI can streamline content creation for marketing across the board.
Ollama Use Case: Learn how Scenario Specialist Dmitri Bagh has utilized Ollama within FME to input data, create custom models, and enhance security protocols. This segment will include demos to illustrate the full capabilities of FME in AI-driven processes.
Custom AI Models: Discover how to leverage FME to build personalized AI models using your data. Whether it’s populating a model with local data for added security or integrating public AI tools, find out how FME facilitates a versatile and secure approach to AI.
We’ll wrap up with a live Q&A session where you can engage with our experts on your specific use cases, and learn more about optimizing your data workflows with AI.
This webinar is ideal for professionals seeking to harness the power of AI within their data management systems while ensuring high levels of customization and security. Whether you're a novice or an expert, gain actionable insights and strategies to elevate your data processes. Join us to see how FME and AI can revolutionize how you work with data!
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This presentation will help you understand the power of Microsoft 365. However, we have mentioned every productivity app included in Office 365. Additionally, we have suggested the migration situation related to Office 365 and how we can help you.
You can also read: https://www.systoolsgroup.com/updates/office-365-tenant-to-tenant-migration-step-by-step-complete-guide/
Apps Break Data
How information systems are built or acquired puts information, which is what they should be about, in a secondary place. Our language adapted accordingly, and we no longer talk about information systems but applications. Applications evolved in a way to break data into diverse fragments, tightly coupled with applications and expensive to integrate. The result is technical debt, which is re-paid by taking even bigger "loans", resulting in an ever-increasing technical debt. Software engineering and procurement practices work in sync with market forces to maintain this trend. This talk demonstrates how natural this situation is. The question is: can something be done to reverse the trend?
June Patch Tuesday
Ivanti’s Patch Tuesday breakdown goes beyond patching your applications and brings you the intelligence and guidance needed to prioritize where to focus your attention first. Catch early analysis on our Ivanti blog, then join industry expert Chris Goettl for the Patch Tuesday Webinar Event. There we’ll do a deep dive into each of the bulletins and give guidance on the risks associated with the newly-identified vulnerabilities.
Freshworks Rethinks NoSQL for Rapid Scaling & Cost-Efficiency
Freshworks creates AI-boosted business software that helps employees work more efficiently and effectively. Managing data across multiple RDBMS and NoSQL databases was already a challenge at their current scale. To prepare for 10X growth, they knew it was time to rethink their database strategy. Learn how they architected a solution that would simplify scaling while keeping costs under control.
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AI & Electronic WarfareHarnessing the Power of NLP and Knowledge Graphs for Opioid Research
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Prompting language models is hard, while programming language models is easy. In this talk, I will discuss the state-of-the-art framework DSPy for programming foundation models with its powerful optimizers and runtime constraint system.
Connector Corner: Seamlessly power UiPath Apps, GenAI with prebuilt connectors
Join us to learn how UiPath Apps can directly and easily interact with prebuilt connectors via Integration Service--including Salesforce, ServiceNow, Open GenAI, and more.
The best part is you can achieve this without building a custom workflow! Say goodbye to the hassle of using separate automations to call APIs. By seamlessly integrating within App Studio, you can now easily streamline your workflow, while gaining direct access to our Connector Catalog of popular applications.
We’ll discuss and demo the benefits of UiPath Apps and connectors including:
Creating a compelling user experience for any software, without the limitations of APIs.
Accelerating the app creation process, saving time and effort
Enjoying high-performance CRUD (create, read, update, delete) operations, for
seamless data management.
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Russell Alfeche, Technology Leader, RPA at qBotic and UiPath MVP
Charlie Greenberg, host
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Read Taking AI to the Next Level in Manufacturing to gain insights on AI adoption in the manufacturing industry, such as:
1. How quickly AI is being implemented in manufacturing.
2. Which barriers stand in the way of AI adoption.
3. How data quality and governance form the backbone of AI.
4. Organizational processes and structures that may inhibit effective AI adoption.
6. Ideas and approaches to help build your organization's AI strategy.
"Choosing proper type of scaling", Olena Syrota
Imagine an IoT processing system that is already quite mature and production-ready and for which client coverage is growing and scaling and performance aspects are life and death questions. The system has Redis, MongoDB, and stream processing based on ksqldb. In this talk, firstly, we will analyze scaling approaches and then select the proper ones for our system.
Your One-Stop Shop for Python Success: Top 10 US Python Development Providers
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HCL Notes and Domino License Cost Reduction in the World of DLAU
Webinar Recording: https://www.panagenda.com/webinars/hcl-notes-and-domino-license-cost-reduction-in-the-world-of-dlau/
The introduction of DLAU and the CCB & CCX licensing model caused quite a stir in the HCL community. As a Notes and Domino customer, you may have faced challenges with unexpected user counts and license costs. You probably have questions on how this new licensing approach works and how to benefit from it. Most importantly, you likely have budget constraints and want to save money where possible. Don’t worry, we can help with all of this!
We’ll show you how to fix common misconfigurations that cause higher-than-expected user counts, and how to identify accounts which you can deactivate to save money. There are also frequent patterns that can cause unnecessary cost, like using a person document instead of a mail-in for shared mailboxes. We’ll provide examples and solutions for those as well. And naturally we’ll explain the new licensing model.
Join HCL Ambassador Marc Thomas in this webinar with a special guest appearance from Franz Walder. It will give you the tools and know-how to stay on top of what is going on with Domino licensing. You will be able lower your cost through an optimized configuration and keep it low going forward.
These topics will be covered
- Reducing license cost by finding and fixing misconfigurations and superfluous accounts
- How do CCB and CCX licenses really work?
- Understanding the DLAU tool and how to best utilize it
- Tips for common problem areas, like team mailboxes, functional/test users, etc
- Practical examples and best practices to implement right away
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In the realm of cybersecurity, offensive security practices act as a critical shield. By simulating real-world attacks in a controlled environment, these techniques expose vulnerabilities before malicious actors can exploit them. This proactive approach allows manufacturers to identify and fix weaknesses, significantly enhancing system security.
This presentation delves into the development of a system designed to mimic Galileo's Open Service signal using software-defined radio (SDR) technology. We'll begin with a foundational overview of both Global Navigation Satellite Systems (GNSS) and the intricacies of digital signal processing.
The presentation culminates in a live demonstration. We'll showcase the manipulation of Galileo's Open Service pilot signal, simulating an attack on various software and hardware systems. This practical demonstration serves to highlight the potential consequences of unaddressed vulnerabilities, emphasizing the importance of offensive security practices in safeguarding critical infrastructure.
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Highly Autonomous Self Learning AI Agent
- 1. HASL : HIGHLY AUTONOUMOUS SELF-LEARNING AI AGENT 1
- 2. OBJECTIVE • To build a real-time occupancy detection system using machine learning neural network • Remotely recognize people’s emotions from video feed and perform prediction analysis • Communicate with security system including CCTV, audio feeds 2
- 3. IDEA AND SCOPE 3 • The detection system recognizes occupants inside an environment with the help of CCTV footages and also camera feeds from occupants smartpho • The system also utilizes machine learning technology to deeply understand the occupants’ emotions, their actions and predict their actions.
- 5. 5 USER SCHEMA • MongoDB – NoSQL Distributed Database • Contains all user information such as – Name – ID – Last Seen – Seen with – Emotion – Status – Location
- 6. 6 SAMPLE USER SCHEMA { "userID": "UID0001", "name": "Raghav", "location": "", "seen with": { "userID": "UID0003, "name": "Vijay", "location": "Tambaram" }, "last seen": "21:01:25 PM", "emotion": "neutral" }
- 7. REQUIREMENTS - HARDWARE • 2.1 GHz or above Intel Quad Core processors ( Quantity – 5 ) • 4 GB RAM ( Quantity – 5 ) • 500GB HDD ( Quantity – 4 ) • NVIDIA 2GB GPU ( Quantity – 2 ) • Network Switch ( Quantity – 1 ) 7
- 8. PERFORMANCE ESTIMATION CPU Clock Speed - 2.1 GHz Operations / Cycle - 4 Cores / Processor - 4 Processors / Node - 2 No. of Nodes - 5 Efficiency ~ 85 % FLOPS Estimate: Theoretical - 0.336 Tflops Real – world - 0.29 Tflops 8
- 9. REQUIREMENTS - SOFTWARE • Unix – based OS ( Ubuntu / CentOS ) •Apache UIMA – content analysis of unstructured data • ConceptNet4, DBPedia, WordNet - for Ontological data • Ngnix / HAProxy – for load balancing • Languages – Java, Python, NodeJS, Haskell, C++ 9
- 10. ALGORITHMS AND FRAMEWORKS • Multimodal Recurrent Neural Networks • Viola-Jones Object detection • Bayesian Networks and Support Vector machines 10
- 11. 11 ARCHITECTURE - NETWORK CAMERA FEEDS MEMCACHED LOAD BALANCER NODE 1 NODE 2 NODE 3 NODE 4 NODE 5
- 12. 12 REFERENCES [1] Probabilistic Modeling of Failure Dependencies Using Markov Logic Networks - Ghosh, S, Steiner.W,, Denker, G - 2013 IEEE 19th Pacific Rim International Conference [2] Probabilistic Logic Networks, A Comprehensive Framework for Uncertain Inference - Goertzel, B., Iklé, M., Goertzel, I.F., Heljakka [3] OpenCog: A Software Framework for Integrative Artificial General Intelligence - Hart, D; B Goertzel (2008). [4] ArtMap: Supervised Real-time learning and classification of non-stationary data by self-organizing neural network – Gail A. Carpenter, Stephen Gossberg [5] ConceptNet 3: a Flexible, Multilingual Semantic Network for Common Sense Knowledge - Catherine Havasi, Rob Speer and Jason Alonso
- 13. 13 THANK YOU !