LLM project deployment plan
•Download as PPT, PDF•
1 like•1,347 views
1) The document outlines a pilot programme for an integrated LLM system across 5 countries to validate its technical viability and effectiveness. 2) It describes the pilot methodology which includes a 1-year programme using various elderly care environments to identify individuals who may benefit. 3) Key metrics are defined to measure technical performance, user acceptance, cognitive/physical outcomes, and market acceptability.
Report
Share
Report
Share
![LLM Pilot Programme Nancy Baker Chief Operating Officer, Global Security Intelligence [email_address]](https://image.slidesharecdn.com/6-llmdeploymentplan-100714071753-phpapp02/85/LLM-project-deployment-plan-1-320.jpg)
![Agenda ,[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],Athens – 20 May 2010](data:image/gif;base64,R0lGODlhAQABAIAAAAAAAP///yH5BAEAAAAALAAAAAABAAEAAAIBRAA7)
Recommended
Episode 2: The LLM / GPT / AI Prompt / Data Engineer Roadmap
In this episode we'll discuss the different flavors of prompt engineering in the LLM/GPT space. According to your skill level you should be able to pick up at any of the following:
Leveling up with GPT
1: Use ChatGPT / GPT Powered Apps
2: Become a Prompt Engineer on ChatGPT/GPT
3: Use GPT API with NoCode Automation, App Builders
4: Create Workflows to Automate Tasks with NoCode
5: Use GPT API with Code, make your own APIs
6: Create Workflows to Automate Tasks with Code
7: Use GPT API with your Data / a Framework
8: Use GPT API with your Data / a Framework to Make your own APIs
9: Create Workflows to Automate Tasks with your Data /a Framework
10: Use Another LLM API other than GPT (Cohere, HuggingFace)
11: Use open source LLM models on your computer
12: Finetune / Build your own models
Series: Using AI / ChatGPT at Work - GPT Automation
Are you a small business owner or web developer interested in leveraging the power of GPT (Generative Pretrained Transformer) technology to enhance your business processes?
If so, Join us for a series of events focused on using GPT in business. Whether you're a small business owner or a web developer, you'll learn how to leverage GPT to improve your workflow and provide better services to your customers.
Introduction to LLMs, Prompt Engineering fundamentals,
- Prompt Engineering fundamentals
- Google Foundations Models
- Advanced Prompting Techniques
- ReAct prompting
- Prompting best practices
- Open source LLM
- Google Gemma
- EU Artificial Intelligence Act
Llama-index
The document describes LlamaIndex, a toolkit that provides indices over unstructured and structured data to augment language models with private data through in-context learning. It discusses how LlamaIndex solves data ingestion and indexing problems to perform language model data augmentation in an efficient manner. Examples of how LlamaIndex can be used with different data connectors like Gmail, audio files, and Notion pages are also provided.
And then there were ... Large Language Models
It is not often even in the ICT world that one witnesses a revolution. The rise of the Personal Computer, the rise of mobile telephony and, of course, the rise of the Internet are some of those revolutions. So what is ChatGPT really? Is ChatGPT also such a revolution? And like any revolution, does ChatGPT have its winners and losers? And who are they? How do we ensure that ChatGPT contributes to a positive impulse for "Smart Humanity?".
During a key note om April 3 and 13 2023 Piek Vossen explained the impact of Large Language Models like ChatGPT.
Prof. PhD. Piek Th.J.M. Vossen, is Full professor of Computational Lexicology at the Faculty of Humanities, Department of Language, Literature and Communication (LCC) at VU Amsterdam:
What is ChatGPT? What technology and thought processes underlie it? What are its consequences? What choices are being made? In the presentation, Piek will elaborate on the basic principles behind Large Language Models and how they are used as a basis for Deep Learning in which they are fine-tuned for specific tasks. He will also discuss a specific variant GPT that underlies ChatGPT. It covers what ChatGPT can and cannot do, what it is good for and what the risks are.
Introduction to Deep Learning (NVIDIA)
NVIDIA compute GPUs and software toolkits are key drivers behind major advancements in machine learning. Of particular interest is a technique called "deep learning", which utilizes what are known as Convolution Neural Networks (CNNs) having landslide success in computer vision and widespread adoption in a variety of fields such as autonomous vehicles, cyber security, and healthcare. In this talk is presented a high level introduction to deep learning where we discuss core concepts, success stories, and relevant use cases. Additionally, we will provide an overview of essential frameworks and workflows for deep learning. Finally, we explore emerging domains for GPU computing such as large-scale graph analytics, in-memory databases.
https://tech.rakuten.co.jp/
Best Python Libraries For Data Science & Machine Learning | Edureka
This document provides an overview of popular Python libraries for data science and machine learning tasks. It discusses libraries for statistical analysis (NumPy, SciPy, Pandas, StatsModels), data visualization (Matplotlib, Seaborn, Plotly, Bokeh), machine learning (Scikit-learn, XGBoost, Eli5), deep learning (TensorFlow, Keras, Pytorch), and natural language processing (NLTK, SpaCy, Gensim). For each category, it lists the top libraries and briefly describes their main functionalities. The document serves as an introduction to the Python data science ecosystem.
Retrieval Augmented Generation in Practice: Scalable GenAI platforms with k8s...
Mihai is the Principal Architect for Platform Engineering and Technology Solutions at IBM, responsible for Cloud Native and AI Solutions. He is a Red Hat Certified Architect, CKA/CKS, a leader in the IBM Open Innovation community, and advocate for open source development. Mihai is driving the development of Retrieval Augmentation Generation platforms, and solutions for Generative AI at IBM that leverage WatsonX, Vector databases, LangChain, HuggingFace and open source AI models.
Mihai will share lessons learned building Retrieval Augmented Generation, or “Chat with Documents” platforms and APIs that scale, and deploy on Kubernetes. His talk will cover use cases for Generative AI, limitations of Large Language Models, use of RAG, Vector Databases and Fine Tuning to overcome model limitations and build solutions that connect to your data and provide content grounding, limit hallucinations and form the basis of explainable AI. In terms of technology, he will cover LLAMA2, HuggingFace TGIS, SentenceTransformers embedding models using Python, LangChain, and Weaviate and ChromaDB vector databases. He’ll also share tips on writing code using LLM, including building an agent for Ansible and containers.
Scaling factors for Large Language Model Architectures:
• Vector Database: consider sharding and High Availability
• Fine Tuning: collecting data to be used for fine tuning
• Governance and Model Benchmarking: how are you testing your model performance
over time, with different prompts, one-shot, and various parameters
• Chain of Reasoning and Agents
• Caching embeddings and responses
• Personalization and Conversational Memory Database
• Streaming Responses and optimizing performance. A fine tuned 13B model may
perform better than a poor 70B one!
• Calling 3rd party functions or APIs for reasoning or other type of data (ex: LLMs are
terrible at reasoning and prediction, consider calling other models)
• Fallback techniques: fallback to a different model, or default answers
• API scaling techniques, rate limiting, etc.
• Async, streaming and parallelization, multiprocessing, GPU acceleration (including
embeddings), generating your API using OpenAPI, etc.
LLMs Bootcamp
This document provides information about a bootcamp to build applications using Large Language Models (LLMs). The bootcamp consists of 11 modules covering topics such as introduction to generative AI, text analytics techniques, neural network models for natural language processing, transformer models, embedding retrieval, semantic search, prompt engineering, fine-tuning LLMs, orchestration frameworks, the LangChain application platform, and a final project to build a custom LLM application. The bootcamp will be held in various locations and dates between September 2023 and January 2024.
Recommended
Episode 2: The LLM / GPT / AI Prompt / Data Engineer Roadmap
In this episode we'll discuss the different flavors of prompt engineering in the LLM/GPT space. According to your skill level you should be able to pick up at any of the following:
Leveling up with GPT
1: Use ChatGPT / GPT Powered Apps
2: Become a Prompt Engineer on ChatGPT/GPT
3: Use GPT API with NoCode Automation, App Builders
4: Create Workflows to Automate Tasks with NoCode
5: Use GPT API with Code, make your own APIs
6: Create Workflows to Automate Tasks with Code
7: Use GPT API with your Data / a Framework
8: Use GPT API with your Data / a Framework to Make your own APIs
9: Create Workflows to Automate Tasks with your Data /a Framework
10: Use Another LLM API other than GPT (Cohere, HuggingFace)
11: Use open source LLM models on your computer
12: Finetune / Build your own models
Series: Using AI / ChatGPT at Work - GPT Automation
Are you a small business owner or web developer interested in leveraging the power of GPT (Generative Pretrained Transformer) technology to enhance your business processes?
If so, Join us for a series of events focused on using GPT in business. Whether you're a small business owner or a web developer, you'll learn how to leverage GPT to improve your workflow and provide better services to your customers.
Introduction to LLMs, Prompt Engineering fundamentals,
- Prompt Engineering fundamentals
- Google Foundations Models
- Advanced Prompting Techniques
- ReAct prompting
- Prompting best practices
- Open source LLM
- Google Gemma
- EU Artificial Intelligence Act
Llama-index
The document describes LlamaIndex, a toolkit that provides indices over unstructured and structured data to augment language models with private data through in-context learning. It discusses how LlamaIndex solves data ingestion and indexing problems to perform language model data augmentation in an efficient manner. Examples of how LlamaIndex can be used with different data connectors like Gmail, audio files, and Notion pages are also provided.
And then there were ... Large Language Models
It is not often even in the ICT world that one witnesses a revolution. The rise of the Personal Computer, the rise of mobile telephony and, of course, the rise of the Internet are some of those revolutions. So what is ChatGPT really? Is ChatGPT also such a revolution? And like any revolution, does ChatGPT have its winners and losers? And who are they? How do we ensure that ChatGPT contributes to a positive impulse for "Smart Humanity?".
During a key note om April 3 and 13 2023 Piek Vossen explained the impact of Large Language Models like ChatGPT.
Prof. PhD. Piek Th.J.M. Vossen, is Full professor of Computational Lexicology at the Faculty of Humanities, Department of Language, Literature and Communication (LCC) at VU Amsterdam:
What is ChatGPT? What technology and thought processes underlie it? What are its consequences? What choices are being made? In the presentation, Piek will elaborate on the basic principles behind Large Language Models and how they are used as a basis for Deep Learning in which they are fine-tuned for specific tasks. He will also discuss a specific variant GPT that underlies ChatGPT. It covers what ChatGPT can and cannot do, what it is good for and what the risks are.
Introduction to Deep Learning (NVIDIA)
NVIDIA compute GPUs and software toolkits are key drivers behind major advancements in machine learning. Of particular interest is a technique called "deep learning", which utilizes what are known as Convolution Neural Networks (CNNs) having landslide success in computer vision and widespread adoption in a variety of fields such as autonomous vehicles, cyber security, and healthcare. In this talk is presented a high level introduction to deep learning where we discuss core concepts, success stories, and relevant use cases. Additionally, we will provide an overview of essential frameworks and workflows for deep learning. Finally, we explore emerging domains for GPU computing such as large-scale graph analytics, in-memory databases.
https://tech.rakuten.co.jp/
Best Python Libraries For Data Science & Machine Learning | Edureka
This document provides an overview of popular Python libraries for data science and machine learning tasks. It discusses libraries for statistical analysis (NumPy, SciPy, Pandas, StatsModels), data visualization (Matplotlib, Seaborn, Plotly, Bokeh), machine learning (Scikit-learn, XGBoost, Eli5), deep learning (TensorFlow, Keras, Pytorch), and natural language processing (NLTK, SpaCy, Gensim). For each category, it lists the top libraries and briefly describes their main functionalities. The document serves as an introduction to the Python data science ecosystem.
Retrieval Augmented Generation in Practice: Scalable GenAI platforms with k8s...
Mihai is the Principal Architect for Platform Engineering and Technology Solutions at IBM, responsible for Cloud Native and AI Solutions. He is a Red Hat Certified Architect, CKA/CKS, a leader in the IBM Open Innovation community, and advocate for open source development. Mihai is driving the development of Retrieval Augmentation Generation platforms, and solutions for Generative AI at IBM that leverage WatsonX, Vector databases, LangChain, HuggingFace and open source AI models.
Mihai will share lessons learned building Retrieval Augmented Generation, or “Chat with Documents” platforms and APIs that scale, and deploy on Kubernetes. His talk will cover use cases for Generative AI, limitations of Large Language Models, use of RAG, Vector Databases and Fine Tuning to overcome model limitations and build solutions that connect to your data and provide content grounding, limit hallucinations and form the basis of explainable AI. In terms of technology, he will cover LLAMA2, HuggingFace TGIS, SentenceTransformers embedding models using Python, LangChain, and Weaviate and ChromaDB vector databases. He’ll also share tips on writing code using LLM, including building an agent for Ansible and containers.
Scaling factors for Large Language Model Architectures:
• Vector Database: consider sharding and High Availability
• Fine Tuning: collecting data to be used for fine tuning
• Governance and Model Benchmarking: how are you testing your model performance
over time, with different prompts, one-shot, and various parameters
• Chain of Reasoning and Agents
• Caching embeddings and responses
• Personalization and Conversational Memory Database
• Streaming Responses and optimizing performance. A fine tuned 13B model may
perform better than a poor 70B one!
• Calling 3rd party functions or APIs for reasoning or other type of data (ex: LLMs are
terrible at reasoning and prediction, consider calling other models)
• Fallback techniques: fallback to a different model, or default answers
• API scaling techniques, rate limiting, etc.
• Async, streaming and parallelization, multiprocessing, GPU acceleration (including
embeddings), generating your API using OpenAPI, etc.
LLMs Bootcamp
This document provides information about a bootcamp to build applications using Large Language Models (LLMs). The bootcamp consists of 11 modules covering topics such as introduction to generative AI, text analytics techniques, neural network models for natural language processing, transformer models, embedding retrieval, semantic search, prompt engineering, fine-tuning LLMs, orchestration frameworks, the LangChain application platform, and a final project to build a custom LLM application. The bootcamp will be held in various locations and dates between September 2023 and January 2024.
How to Make a Chatbot in Python | Edureka
The document discusses chatbots and how to create one using Python. A chatbot is a program that simulates conversation between a user and computer. The ChatterBot library in Python allows for creating chatbots through automated responses, machine learning algorithms, and training on language data. It takes in user input, processes it to return the most confident response, and can be implemented in a Flask web application for conversational use.
What is MLOps
A brief introduction to MLOps (machine learning operations). For more, check out our other MLOps materials on valohai.com/mlops
Introduction to ChatGPT & how its implemented in UiPath
This document provides an overview of using ChatGPT for intelligent automation through UiPath. It discusses how ChatGPT can be implemented in UiPath using web API activities. It also covers the benefits and limitations of using ChatGPT, as well as best practices for developing ChatGPT models and considerations for privacy, ethics, security and governance. The document concludes with information on UiPath's community resources for learning RPA skills and connecting with other automation professionals.
AI and ML Series - Introduction to Generative AI and LLMs - Session 1
Session 1
👉This first session will cover an introduction to Generative AI & harnessing the power of large language models. The following topics will be discussed:
Introduction to Generative AI & harnessing the power of large language models.
What’s generative AI & what’s LLM.
How are we using it in our document understanding & communication mining models?
How to develop a trustworthy and unbiased AI model using LLM & GenAI.
Personal Intelligent Assistant
Speakers:
📌George Roth - AI Evangelist at UiPath
📌Sharon Palawandram - Senior Machine Learning Consultant @ Ashling Partners & UiPath MVP
📌Russel Alfeche - Technology Leader RPA @qBotica & UiPath MVP
ChatGPT - What works and what doesn't
Oh my gosh - the hype about ChatGPT is massive. Let's look at five examples of ChatGPT in use and evaluate whether it is actually a good solution.
This talk outlines the risks, limitations and potential of the tool.
ChatGPT works well in some content contexts but very poorly in others.
Prompt Engineering Guide.pptx
An expert in prompt engineering provides guidelines on designing effective prompts for natural language models. The document discusses prompt engineering principles, what makes a good prompt, and various prompt frameworks including priming, focused prompts, and practical everyday prompts. Effective prompts are clear, concise, unambiguous, and provide the necessary context and task to generate a desired response from a model. Iteration and adapting the prompt based on the response is important.
What Is GPT-3 And Why Is It Revolutionizing Artificial Intelligence?
GPT-3 is an AI tool created by OpenAI that can generate text in human-like ways. It has been trained on vast amounts of text from the internet. GPT-3 can answer questions, summarize text, translate languages, and generate computer code. However, it has limitations as its output can become gibberish for complex tasks and it operates as a black box system. While impressive, GPT-3 is just an early glimpse of what advanced AI may be able to accomplish.
ChatGPT.pptx
ChatGPT is a natural language processing model created by OpenAI that can generate human-like responses to text-based conversations. It uses deep learning and was pre-trained on vast amounts of text to understand language. Performance is evaluated using metrics like perplexity, accuracy, fluency and human evaluation. While very powerful, ChatGPT and other large language models raise legal and ethical concerns regarding copyright, privacy, bias and how training data was obtained. The future potential includes using conversational AI to streamline operations in areas like data entry, scheduling and customer service.
How to Build an App with ChatGPT.pdf
ChatGPT is a highly advanced tool that allows non-technical users access to powerful capabilities and reduces the time required to develop applications. Consider that we want to build a to-do list application using React Native. Now with the help of ChatGPT, we will start the development process.
Pre trained language model
The document discusses recent developments in pre-trained language models including ELMO, ULMFiT, BERT, and GPT-2. It provides overviews of the core structures and implementations of each model, noting that they have achieved great performance on natural language tasks without requiring labeled data for pre-training, similar to how pre-training helps in computer vision tasks. The document also includes a comparison chart of the types of natural language tasks each model can perform.
An Introduction to Generative AI
For this plenary talk at the Charlotte AI Institute for Smarter Learning, Dr. Cori Faklaris introduces her fellow college educators to the exciting world of generative AI tools. She gives a high-level overview of the generative AI landscape and how these tools use machine learning algorithms to generate creative content such as music, art, and text. She then shares some examples of generative AI tools and demonstrate how she has used some of these tools to enhance teaching and learning in the classroom and to boost her productivity in other areas of academic life.
An Introduction to Generative AI - May 18, 2023
For this plenary talk at the Charlotte AI Institute for Smarter Learning, Dr. Cori Faklaris introduces her fellow college educators to the exciting world of generative AI tools. She gives a high-level overview of the generative AI landscape and how these tools use machine learning algorithms to generate creative content such as music, art, and text. She then shares some examples of generative AI tools and demonstrate how she has used some of these tools to enhance teaching and learning in the classroom and to boost her productivity in other areas of academic life.
Generative-AI-in-enterprise-20230615.pdf
This document discusses generative AI and its potential transformations and use cases. It outlines how generative AI could enable more low-cost experimentation, blur division boundaries, and allow "talking to data" for innovation and operational excellence. The document also references responsible AI frameworks and a pattern catalogue for developing foundation model-based systems. Potential use cases discussed include automated reporting, digital twins, data integration, operation planning, communication, and innovation applications like surrogate models and cross-discipline synthesis.
Detection Datasets: Forged Characters for Passport and Driving Licence
Forged characters detection from personal documents including a passport or a driving licence is an extremely important and challenging task in digital image forensics, as forged information on personal documents can be used for fraud purposes including theft, robbery etc. For any detection task i.e. forged character detection, deep learning models are data hungry and getting the forged characters dataset for personal documents is very difficult due to various reasons, including information privacy, unlabeled data or existing work is evaluated on private datasets with limited access and getting data labelled is another big challenge. To address these issues, we propose a new algorithm that generates two new datasets named forged characters detection on passport (FCD-P) and forged characters detection on driving licence (FCD-D). To the best of our knowledge, we are the first to release these datasets. The proposed algorithm first reads the plain image, then performs forging tasks i.e. randomly changes the position of the random character or randomly adds little noise. At the same time, the algorithm also records the bounding boxes of the forged characters. To meet real world situations, we perform multiple data augmentation on cards very carefully. Overall, each dataset consists of 15000 images, each image with size of 950 x 550. Our algorithm code, FCD-P and FCD-D are publicly available.
Automate your Job and Business with ChatGPT #3 - Fundamentals of LLM/GPT
This document provides an agenda for a full-day bootcamp on large language models (LLMs) like GPT-3. The bootcamp will cover fundamentals of machine learning and neural networks, the transformer architecture, how LLMs work, and popular LLMs beyond ChatGPT. The agenda includes sessions on LLM strategy and theory, design patterns for LLMs, no-code/code stacks for LLMs, and building a custom chatbot with an LLM and your own data.
Using Generative AI to Assess the Quality of Open-Ended Responses in Surveys
The document discusses using generative AI to assess the quality of open-ended survey responses. It outlines current challenges with open-ended responses, how generative AI can help through natural language processing, and best practices for implementation. Specifically, it provides an example of using ChatGPT to analyze sample open-ended responses and discusses setting up a Google Sheet to automate the process at scale and continuously improve the model through iterative training.
Practitioner's Guide to LLMs: Exploring Use Cases and a Glimpse Beyond Curren...
Pascal Pfeiffer, Principal Data Scientist, H2O.ai
H2O Open Source GenAI World SF 2023
This talk dives into the expansive ecosystem of Large Language Models (LLMs), offering practitioners an insightful guide to various relevant applications, from natural language understanding to creative content generation. While exploring use cases across different industries, it also honestly addresses the current limitations of LLMs and anticipates future advancements.
Introduction to Data Science & Python.pdf
This document provides an introduction to data science, including what it is, its components and uses. It discusses the life cycle and tasks of a data scientist. It also covers Python as a programming language for data science, how to install Anaconda and Jupyter Notebook, basic Python concepts like data types, functions and statements. Key tools like Anaconda and Jupyter Notebook are introduced for working with Python for data analysis and visualization.
Retrieval-Augmented Generation for Knowledge-Intensive NLP Tasks.pdf
The document describes the RAG (Retrieval-Augmented Generation) model for knowledge-intensive NLP tasks. RAG combines a pre-trained language generator (BART) with a dense passage retriever (DPR) to retrieve and incorporate relevant knowledge from Wikipedia. RAG achieves state-of-the-art results on open-domain question answering, abstractive question answering, and fact verification by leveraging both parametric knowledge from the generator and non-parametric knowledge retrieved from Wikipedia. The retrieved knowledge can also be updated without retraining the model.
What is the llm service why use it? (scientific and technical issues)
Long Lasting Memories (LLM) is an integrated ICT platform that combines cognitive exercises, physical activity, and ambient assisted living to support elderly health and independent living. It has three main components: an independent living component, cognitive training component, and physical training component, connected through a central management system. The LLM platform will be evaluated through pilots in 5 European countries to test its usability, health impacts, and market potential.
Long Lasting Memories Project Presentation
LLM is an integrated ICT platform which combines state-of-the-art cognitive exercises with physical activity in the framework of an advanced ambient assisted living environment.
More Related Content
What's hot
How to Make a Chatbot in Python | Edureka
The document discusses chatbots and how to create one using Python. A chatbot is a program that simulates conversation between a user and computer. The ChatterBot library in Python allows for creating chatbots through automated responses, machine learning algorithms, and training on language data. It takes in user input, processes it to return the most confident response, and can be implemented in a Flask web application for conversational use.
What is MLOps
A brief introduction to MLOps (machine learning operations). For more, check out our other MLOps materials on valohai.com/mlops
Introduction to ChatGPT & how its implemented in UiPath
This document provides an overview of using ChatGPT for intelligent automation through UiPath. It discusses how ChatGPT can be implemented in UiPath using web API activities. It also covers the benefits and limitations of using ChatGPT, as well as best practices for developing ChatGPT models and considerations for privacy, ethics, security and governance. The document concludes with information on UiPath's community resources for learning RPA skills and connecting with other automation professionals.
AI and ML Series - Introduction to Generative AI and LLMs - Session 1
Session 1
👉This first session will cover an introduction to Generative AI & harnessing the power of large language models. The following topics will be discussed:
Introduction to Generative AI & harnessing the power of large language models.
What’s generative AI & what’s LLM.
How are we using it in our document understanding & communication mining models?
How to develop a trustworthy and unbiased AI model using LLM & GenAI.
Personal Intelligent Assistant
Speakers:
📌George Roth - AI Evangelist at UiPath
📌Sharon Palawandram - Senior Machine Learning Consultant @ Ashling Partners & UiPath MVP
📌Russel Alfeche - Technology Leader RPA @qBotica & UiPath MVP
ChatGPT - What works and what doesn't
Oh my gosh - the hype about ChatGPT is massive. Let's look at five examples of ChatGPT in use and evaluate whether it is actually a good solution.
This talk outlines the risks, limitations and potential of the tool.
ChatGPT works well in some content contexts but very poorly in others.
Prompt Engineering Guide.pptx
An expert in prompt engineering provides guidelines on designing effective prompts for natural language models. The document discusses prompt engineering principles, what makes a good prompt, and various prompt frameworks including priming, focused prompts, and practical everyday prompts. Effective prompts are clear, concise, unambiguous, and provide the necessary context and task to generate a desired response from a model. Iteration and adapting the prompt based on the response is important.
What Is GPT-3 And Why Is It Revolutionizing Artificial Intelligence?
GPT-3 is an AI tool created by OpenAI that can generate text in human-like ways. It has been trained on vast amounts of text from the internet. GPT-3 can answer questions, summarize text, translate languages, and generate computer code. However, it has limitations as its output can become gibberish for complex tasks and it operates as a black box system. While impressive, GPT-3 is just an early glimpse of what advanced AI may be able to accomplish.
ChatGPT.pptx
ChatGPT is a natural language processing model created by OpenAI that can generate human-like responses to text-based conversations. It uses deep learning and was pre-trained on vast amounts of text to understand language. Performance is evaluated using metrics like perplexity, accuracy, fluency and human evaluation. While very powerful, ChatGPT and other large language models raise legal and ethical concerns regarding copyright, privacy, bias and how training data was obtained. The future potential includes using conversational AI to streamline operations in areas like data entry, scheduling and customer service.
How to Build an App with ChatGPT.pdf
ChatGPT is a highly advanced tool that allows non-technical users access to powerful capabilities and reduces the time required to develop applications. Consider that we want to build a to-do list application using React Native. Now with the help of ChatGPT, we will start the development process.
Pre trained language model
The document discusses recent developments in pre-trained language models including ELMO, ULMFiT, BERT, and GPT-2. It provides overviews of the core structures and implementations of each model, noting that they have achieved great performance on natural language tasks without requiring labeled data for pre-training, similar to how pre-training helps in computer vision tasks. The document also includes a comparison chart of the types of natural language tasks each model can perform.
An Introduction to Generative AI
For this plenary talk at the Charlotte AI Institute for Smarter Learning, Dr. Cori Faklaris introduces her fellow college educators to the exciting world of generative AI tools. She gives a high-level overview of the generative AI landscape and how these tools use machine learning algorithms to generate creative content such as music, art, and text. She then shares some examples of generative AI tools and demonstrate how she has used some of these tools to enhance teaching and learning in the classroom and to boost her productivity in other areas of academic life.
An Introduction to Generative AI - May 18, 2023
For this plenary talk at the Charlotte AI Institute for Smarter Learning, Dr. Cori Faklaris introduces her fellow college educators to the exciting world of generative AI tools. She gives a high-level overview of the generative AI landscape and how these tools use machine learning algorithms to generate creative content such as music, art, and text. She then shares some examples of generative AI tools and demonstrate how she has used some of these tools to enhance teaching and learning in the classroom and to boost her productivity in other areas of academic life.
Generative-AI-in-enterprise-20230615.pdf
This document discusses generative AI and its potential transformations and use cases. It outlines how generative AI could enable more low-cost experimentation, blur division boundaries, and allow "talking to data" for innovation and operational excellence. The document also references responsible AI frameworks and a pattern catalogue for developing foundation model-based systems. Potential use cases discussed include automated reporting, digital twins, data integration, operation planning, communication, and innovation applications like surrogate models and cross-discipline synthesis.
Detection Datasets: Forged Characters for Passport and Driving Licence
Forged characters detection from personal documents including a passport or a driving licence is an extremely important and challenging task in digital image forensics, as forged information on personal documents can be used for fraud purposes including theft, robbery etc. For any detection task i.e. forged character detection, deep learning models are data hungry and getting the forged characters dataset for personal documents is very difficult due to various reasons, including information privacy, unlabeled data or existing work is evaluated on private datasets with limited access and getting data labelled is another big challenge. To address these issues, we propose a new algorithm that generates two new datasets named forged characters detection on passport (FCD-P) and forged characters detection on driving licence (FCD-D). To the best of our knowledge, we are the first to release these datasets. The proposed algorithm first reads the plain image, then performs forging tasks i.e. randomly changes the position of the random character or randomly adds little noise. At the same time, the algorithm also records the bounding boxes of the forged characters. To meet real world situations, we perform multiple data augmentation on cards very carefully. Overall, each dataset consists of 15000 images, each image with size of 950 x 550. Our algorithm code, FCD-P and FCD-D are publicly available.
Automate your Job and Business with ChatGPT #3 - Fundamentals of LLM/GPT
This document provides an agenda for a full-day bootcamp on large language models (LLMs) like GPT-3. The bootcamp will cover fundamentals of machine learning and neural networks, the transformer architecture, how LLMs work, and popular LLMs beyond ChatGPT. The agenda includes sessions on LLM strategy and theory, design patterns for LLMs, no-code/code stacks for LLMs, and building a custom chatbot with an LLM and your own data.
Using Generative AI to Assess the Quality of Open-Ended Responses in Surveys
The document discusses using generative AI to assess the quality of open-ended survey responses. It outlines current challenges with open-ended responses, how generative AI can help through natural language processing, and best practices for implementation. Specifically, it provides an example of using ChatGPT to analyze sample open-ended responses and discusses setting up a Google Sheet to automate the process at scale and continuously improve the model through iterative training.
Practitioner's Guide to LLMs: Exploring Use Cases and a Glimpse Beyond Curren...
Pascal Pfeiffer, Principal Data Scientist, H2O.ai
H2O Open Source GenAI World SF 2023
This talk dives into the expansive ecosystem of Large Language Models (LLMs), offering practitioners an insightful guide to various relevant applications, from natural language understanding to creative content generation. While exploring use cases across different industries, it also honestly addresses the current limitations of LLMs and anticipates future advancements.
Introduction to Data Science & Python.pdf
This document provides an introduction to data science, including what it is, its components and uses. It discusses the life cycle and tasks of a data scientist. It also covers Python as a programming language for data science, how to install Anaconda and Jupyter Notebook, basic Python concepts like data types, functions and statements. Key tools like Anaconda and Jupyter Notebook are introduced for working with Python for data analysis and visualization.
Retrieval-Augmented Generation for Knowledge-Intensive NLP Tasks.pdf
The document describes the RAG (Retrieval-Augmented Generation) model for knowledge-intensive NLP tasks. RAG combines a pre-trained language generator (BART) with a dense passage retriever (DPR) to retrieve and incorporate relevant knowledge from Wikipedia. RAG achieves state-of-the-art results on open-domain question answering, abstractive question answering, and fact verification by leveraging both parametric knowledge from the generator and non-parametric knowledge retrieved from Wikipedia. The retrieved knowledge can also be updated without retraining the model.
What's hot (20)
Introduction to ChatGPT & how its implemented in UiPath
Introduction to ChatGPT & how its implemented in UiPath
AI and ML Series - Introduction to Generative AI and LLMs - Session 1
AI and ML Series - Introduction to Generative AI and LLMs - Session 1
What Is GPT-3 And Why Is It Revolutionizing Artificial Intelligence?
What Is GPT-3 And Why Is It Revolutionizing Artificial Intelligence?
(E book) cracking & hacking tutorial 1000 pagine (ita)
(E book) cracking & hacking tutorial 1000 pagine (ita)
Detection Datasets: Forged Characters for Passport and Driving Licence
Detection Datasets: Forged Characters for Passport and Driving Licence
Automate your Job and Business with ChatGPT #3 - Fundamentals of LLM/GPT
Automate your Job and Business with ChatGPT #3 - Fundamentals of LLM/GPT
Using Generative AI to Assess the Quality of Open-Ended Responses in Surveys
Using Generative AI to Assess the Quality of Open-Ended Responses in Surveys
Practitioner's Guide to LLMs: Exploring Use Cases and a Glimpse Beyond Curren...
Practitioner's Guide to LLMs: Exploring Use Cases and a Glimpse Beyond Curren...
Retrieval-Augmented Generation for Knowledge-Intensive NLP Tasks.pdf
Retrieval-Augmented Generation for Knowledge-Intensive NLP Tasks.pdf
Similar to LLM project deployment plan
What is the llm service why use it? (scientific and technical issues)
Long Lasting Memories (LLM) is an integrated ICT platform that combines cognitive exercises, physical activity, and ambient assisted living to support elderly health and independent living. It has three main components: an independent living component, cognitive training component, and physical training component, connected through a central management system. The LLM platform will be evaluated through pilots in 5 European countries to test its usability, health impacts, and market potential.
Long Lasting Memories Project Presentation
LLM is an integrated ICT platform which combines state-of-the-art cognitive exercises with physical activity in the framework of an advanced ambient assisted living environment.
Long Lasting Memories (LLM) Project Presentation
The document summarizes Long Lasting Memories (LLM), an integrated ICT platform that combines cognitive exercises, physical activity, and ambient assisted living to support independent living for senior citizens. LLM integrates existing cognitive training and independent living solutions with physical training equipment. It will be tested through trials in 5 countries to evaluate its impact on cognitive and physical health, usability, and market potential. The trials will assess outcomes such as cognitive function, quality of life, and user satisfaction to analyze LLM's efficacy and ability to be widely deployed.
Implementing eHealth: from pilot to practice
Pilots of eHealth services often remain small or are discontinued due to various limitations in assessing their effectiveness and integrating them fully into care. A comprehensive evaluation tool called MAST assesses eHealth services across clinical, economic, user and organizational impacts to determine their potential for scale-up. Catalonia uses MAST to evaluate pilots, certify their interoperability, deploy necessary infrastructure to support scale-up, and conduct ongoing monitoring as services expand. This process helps decision-makers scale effective eHealth services that improve care in a sustainable way.
CRISP WP3 stakeholder workshop
CRISP project works towards building a certification scheme for video surveillance systems, based on the evaluation of their social impact. The slides present findings from the stakeholder analysis phase of the project.
TheFSM project presentation at the BDVA workshop for Data Platform Projects
A presentation for the progress and lessons learned during the first 18 months of the TheFSM project implementation.
MeAC 2: overall results - presentation at INCOM meeting
“Monitoring eAccessibility in Europe 2010-2011”
MEAC 2 Study
General presentation on relevant results, specific reports and recommendations for future studies on monitoring eAccessibility
ICOH 2015 - EU OSH Strategies and national examples
ICOH 2015 - EU OSH Strategies and national examplesEuropean Agency for Safety and Health at Work - EU-OSHA
A policy development session on OSH in Asian Countries at the 31st International Congress on Occupational Health (ICOH) Seoul.CountrySTAT / FENIX Follow-up actions 25 – 26 June 2015 FAO HQ, Rome
Stocktaking and Lessons Learnt from the Implementation of CountrySTAT for the ECO Countries 25 – 26 June 2015 FAO HQ, Rome, Italy
Fabio Grita
CountrySTAT team leader
FAO Statistics Division
© FAO: http://www.fao.org
Caveon Webinar Series: Lessons Learned from EATP and CSDPTF November 2013
Presented by Dr. John Fremer, Dennis Maynes and Steve Addicott, Caveon Test Security
Two important industry conferences have been held in the last couple of months, the European Association of Test Publishers (E-ATP) Conference and the Conference on Statistical Detection of Potential Test Fraud (CSDPTF). Caveon was at both of these events and wants to share some important information with you.
Join Dr. John Fremer, President of Caveon Consulting Services, Steve Addicott, Vice President, Sales and Marketing, and Dennis Maynes, Chief Scientist, Caveon Data Forensics, who attended both conferences and presented sessions. They will explore key takeaways and lessons learned on security. Stay updated on the latest and greatest industry security trends.
EuroPriSe and ISDP10003 2015 -
This document summarizes several certification models that are relevant for demonstrating compliance with the GDPR, including the European Privacy Seal (EuroPriSe) and the International Scheme for Data Protection ISDP©10003. EuroPriSe was developed as an EU-wide certification, while ISDP©10003 was created in 2015 and has an international scope. Both certification models evaluate an organization's processes, products, and services to ensure personal data and privacy are handled according to EU regulations. The document also discusses characteristics of different certification models, including their scope, normative criteria, and relevant standards.
EuroPriSe and ISDP 10003 2015
The document discusses various certification models for ensuring accountability and compliance with the GDPR. It describes EuroPrise and ISDP10003:2015 as examples of certification schemes that aim to provide accountability through a transparent certification process (EuroPrise), and through establishing technical and organizational measures and controls across an organization's data protection processes (ISDP10003). It also analyzes different certification models based on their scope - whether they take a multi-sector or single-sector approach, operate at an international, national or sub-national level, and whether they provide comprehensive certification of all GDPR aspects or focus on single issues.
CRISP Stakeholder Analysis
Findings from Work Package 3 of the CRISP project. Analysis of stakeholder needs from and views on proposed CRISP certification scheme for security products, systems and services.
How to use the EUnetHTA submission template to support production of core Hea...
The document discusses the development of a submission template by the EUnetHTA to support health technology assessments and reimbursement decisions across European countries. It describes analyzing evidence requirements from 33 countries to identify common information requests. Based on this, a draft template was created addressing key domains like the health problem, technology description, clinical effectiveness and safety. The template categories information under common themes and is being piloted and validated before dissemination. It aims to streamline the process of providing evidence to support assessments and reimbursement while allowing flexibility for country-specific needs.
Gabriel Rissola: "Measuring the impact of eInclusion actors"
This document outlines a proposed impact assessment study of organizations that promote digital inclusion and literacy in Europe. The study would (1) identify and classify different types of "eInclusion intermediaries" and their roles, (2) develop standard indicators and methodology to measure the socioeconomic impact of these organizations, and (3) deploy the framework to measure changes in digital skills, employment, and social inclusion as a result of intermediaries' interventions. The goal is to provide evidence of their impact to inform the European Commission's digital agenda policies. Preparatory work would include literature reviews, indicator identification, and stakeholder consultation to design the assessment approach.
EUnetHTA Training course for Stakeholders - Key principles of Health Technolo...
2nd WP2 F-t-F training Course for all EUnetHTA stakeholders - EUnetHTA Tools and Methodology. Roma, 29 Oct. 2014
Trust and security technologies: Lessons from the CRISP project
These slides present findings from Work Package 3 of the CRISP project. CRISPaims to develop an innovative evaluation and certification methodology for security products. This talk was given at the 7th Biennial Surveillance & Society Conference in Barcelona in April 2016.
Can Trust In Security TEchnologies be Enhanced through Certification?
Thordis Sveinsdottir presented work from the CRISP project at the 7th Biennial Surveillance & Society Conference in Barcelona in April 2016.
Tien3
This document discusses training and technology transfer experiences from a European Union perspective in the Asia-Pacific region. It describes the NeSC Training, Outreach and Education projects which have provided training courses worldwide since 2004. Barriers to and enablers of technology adoption are examined based on interviews with researchers. Examples of interventions to address barriers include targeted events, introductory materials, and 'eRoadshows' to disseminate information directly to communities. A model for an online International Winter School for Grid Computing is presented as an example of leveraging resources and services to replicate an in-person training program.
04_a_CEPEJ(2021)5 EN - CEPEJ roadmap certification AI (1).docx
This document outlines a roadmap for introducing a labelling mechanism within the CEPEJ to certify artificial intelligence tools and services used in the justice system. The proposed mechanism would involve setting up a labelling committee, defining label requirements, and establishing an application process. It would aim to promote compliance with the CEPEJ's Ethical Charter on AI through a simplified voluntary certification system. The roadmap describes necessary strategic, operational, and technical steps as well as anticipated resource needs to implement the labelling mechanism.
Similar to LLM project deployment plan (20)
What is the llm service why use it? (scientific and technical issues)
What is the llm service why use it? (scientific and technical issues)
TheFSM project presentation at the BDVA workshop for Data Platform Projects
TheFSM project presentation at the BDVA workshop for Data Platform Projects
MeAC 2: overall results - presentation at INCOM meeting
MeAC 2: overall results - presentation at INCOM meeting
ICOH 2015 - EU OSH Strategies and national examples
ICOH 2015 - EU OSH Strategies and national examples
CountrySTAT / FENIX Follow-up actions 25 – 26 June 2015 FAO HQ, Rome
CountrySTAT / FENIX Follow-up actions 25 – 26 June 2015 FAO HQ, Rome
Caveon Webinar Series: Lessons Learned from EATP and CSDPTF November 2013
Caveon Webinar Series: Lessons Learned from EATP and CSDPTF November 2013
How to use the EUnetHTA submission template to support production of core Hea...
How to use the EUnetHTA submission template to support production of core Hea...
Gabriel Rissola: "Measuring the impact of eInclusion actors"
Gabriel Rissola: "Measuring the impact of eInclusion actors"
EUnetHTA Training course for Stakeholders - Key principles of Health Technolo...
EUnetHTA Training course for Stakeholders - Key principles of Health Technolo...
Trust and security technologies: Lessons from the CRISP project
Trust and security technologies: Lessons from the CRISP project
Can Trust In Security TEchnologies be Enhanced through Certification?
Can Trust In Security TEchnologies be Enhanced through Certification?
04_a_CEPEJ(2021)5 EN - CEPEJ roadmap certification AI (1).docx
04_a_CEPEJ(2021)5 EN - CEPEJ roadmap certification AI (1).docx
More from long lasting memories
LongLastingMemories final presentation
The document summarizes the Long Lasting Memories (LLM) project, which integrated cognitive exercises, physical activity, and ambient assisted living to support independent living for seniors. The LLM platform combined three existing ICT solutions and was tested across multiple countries. Key objectives included integrating the solutions, demonstrating impact, verifying feasibility, and ensuring sustainability. Lessons learned included that combined cognitive and physical training led to memory improvements, users found the system engaging and it improved autonomy and social engagement. The project concluded the LLM deployment is feasible and positive.
Legal and ethical issues (the LLM project)
The document discusses the legal and ethical issues surrounding research applied across two dimensions: pilot deployment and operational deployment. Standards were established to encrypt anonymized user data in pilot deployments and flexible server models were developed to enable multi-country data aggregation. Pilots were conducted internally based on clinical trial standards to ensure user privacy, anonymity, and consistent informed consent. Key documents produced include a report on national and European legislation available for the public, technical specifications for user privacy that are confidential, and ethical guidelines and security reports still in progress for public dissemination.
Physical Training Component (the FitForAll exergame platform)
Fit For All is a is a game platform that can help elderly people to exercise and maintain their physical status and well being through an innovative, low-cost ICT platform, such as Wii Balance Board. The main scope of the research conducted and presented here, is the design and development of a game-like interface that incorporates the characteristics of a Human-Computer Interaction system such as user input and system feedback according to user's movement patterns and the investigation of how such a platform could meet the special needs of a target group, such as elderly people and its potential use as a physical training platform in general.
Cognitive Training Component (Gradior software)
The document describes the Gradior cognitive training software. It consists of four modules for clinical management, treatment management, reporting, and rehabilitation sessions. It allows therapists to establish individualized treatment regimes for patients and monitors their performance over time through exercises targeting areas like attention, memory, perception, and reasoning. The software is designed to be low-cost and accessible to use on basic computers.
Cognitive Training Component (Brainfitness program)
Negative cortical plasticity in aging has four mutually reinforcing components: 1) Noisy processing due to deterioration of sensory organs, 2) Poor signal quality received by the cortex, 3) The brain must adjust by lengthening integration times, slowing processing. 4) This leads to reduced brain activity, engagement in difficult tasks, and less stimulation for attention and reward. Behavioral changes then accelerate cognitive decline. Plasticity-based cognitive training can drive large-scale brain plasticity by refining stimulus processing, using complex inputs, engaging in intense schedules of activity, and positively reinforcing enhanced function. Studies show such training improves auditory memory and processing speed in the elderly.
More from long lasting memories (6)
Physical Training Component (the FitForAll exergame platform)
Physical Training Component (the FitForAll exergame platform)
Cognitive Training Component (Brainfitness program)
Cognitive Training Component (Brainfitness program)
Recently uploaded
Observability Concepts EVERY Developer Should Know -- DeveloperWeek Europe.pdf
Monitoring and observability aren’t traditionally found in software curriculums and many of us cobble this knowledge together from whatever vendor or ecosystem we were first introduced to and whatever is a part of your current company’s observability stack.
While the dev and ops silo continues to crumble….many organizations still relegate monitoring & observability as the purview of ops, infra and SRE teams. This is a mistake - achieving a highly observable system requires collaboration up and down the stack.
I, a former op, would like to extend an invitation to all application developers to join the observability party will share these foundational concepts to build on:
Video Streaming: Then, Now, and in the Future
In his public lecture, Christian Timmerer provides insights into the fascinating history of video streaming, starting from its humble beginnings before YouTube to the groundbreaking technologies that now dominate platforms like Netflix and ORF ON. Timmerer also presents provocative contributions of his own that have significantly influenced the industry. He concludes by looking at future challenges and invites the audience to join in a discussion.
Presentation of the OECD Artificial Intelligence Review of Germany
Consult the full report at https://www.oecd.org/digital/oecd-artificial-intelligence-review-of-germany-609808d6-en.htm
Full-RAG: A modern architecture for hyper-personalization
Mike Del Balso, CEO & Co-Founder at Tecton, presents "Full RAG," a novel approach to AI recommendation systems, aiming to push beyond the limitations of traditional models through a deep integration of contextual insights and real-time data, leveraging the Retrieval-Augmented Generation architecture. This talk will outline Full RAG's potential to significantly enhance personalization, address engineering challenges such as data management and model training, and introduce data enrichment with reranking as a key solution. Attendees will gain crucial insights into the importance of hyperpersonalization in AI, the capabilities of Full RAG for advanced personalization, and strategies for managing complex data integrations for deploying cutting-edge AI solutions.
AI 101: An Introduction to the Basics and Impact of Artificial Intelligence
Imagine a world where machines not only perform tasks but also learn, adapt, and make decisions. This is the promise of Artificial Intelligence (AI), a technology that's not just enhancing our lives but revolutionizing entire industries.
Best 20 SEO Techniques To Improve Website Visibility In SERP
Boost your website's visibility with proven SEO techniques! Our latest blog dives into essential strategies to enhance your online presence, increase traffic, and rank higher on search engines. From keyword optimization to quality content creation, learn how to make your site stand out in the crowded digital landscape. Discover actionable tips and expert insights to elevate your SEO game.
Cosa hanno in comune un mattoncino Lego e la backdoor XZ?
ABSTRACT: A prima vista, un mattoncino Lego e la backdoor XZ potrebbero avere in comune il fatto di essere entrambi blocchi di costruzione, o dipendenze di progetti creativi e software. La realtà è che un mattoncino Lego e il caso della backdoor XZ hanno molto di più di tutto ciò in comune.
Partecipate alla presentazione per immergervi in una storia di interoperabilità, standard e formati aperti, per poi discutere del ruolo importante che i contributori hanno in una comunità open source sostenibile.
BIO: Sostenitrice del software libero e dei formati standard e aperti. È stata un membro attivo dei progetti Fedora e openSUSE e ha co-fondato l'Associazione LibreItalia dove è stata coinvolta in diversi eventi, migrazioni e formazione relativi a LibreOffice. In precedenza ha lavorato a migrazioni e corsi di formazione su LibreOffice per diverse amministrazioni pubbliche e privati. Da gennaio 2020 lavora in SUSE come Software Release Engineer per Uyuni e SUSE Manager e quando non segue la sua passione per i computer e per Geeko coltiva la sua curiosità per l'astronomia (da cui deriva il suo nickname deneb_alpha).
20240609 QFM020 Irresponsible AI Reading List May 2024
Everything I found interesting about the irresponsible use of machine intelligence in May 2024
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
GraphSummit Singapore | The Future of Agility: Supercharging Digital Transfor...
Leonard Jayamohan, Partner & Generative AI Lead, Deloitte
This keynote will reveal how Deloitte leverages Neo4j’s graph power for groundbreaking digital twin solutions, achieving a staggering 100x performance boost. Discover the essential role knowledge graphs play in successful generative AI implementations. Plus, get an exclusive look at an innovative Neo4j + Generative AI solution Deloitte is developing in-house.
Removing Uninteresting Bytes in Software Fuzzing
Imagine a world where software fuzzing, the process of mutating bytes in test seeds to uncover hidden and erroneous program behaviors, becomes faster and more effective. A lot depends on the initial seeds, which can significantly dictate the trajectory of a fuzzing campaign, particularly in terms of how long it takes to uncover interesting behaviour in your code. We introduce DIAR, a technique designed to speedup fuzzing campaigns by pinpointing and eliminating those uninteresting bytes in the seeds. Picture this: instead of wasting valuable resources on meaningless mutations in large, bloated seeds, DIAR removes the unnecessary bytes, streamlining the entire process.
In this work, we equipped AFL, a popular fuzzer, with DIAR and examined two critical Linux libraries -- Libxml's xmllint, a tool for parsing xml documents, and Binutil's readelf, an essential debugging and security analysis command-line tool used to display detailed information about ELF (Executable and Linkable Format). Our preliminary results show that AFL+DIAR does not only discover new paths more quickly but also achieves higher coverage overall. This work thus showcases how starting with lean and optimized seeds can lead to faster, more comprehensive fuzzing campaigns -- and DIAR helps you find such seeds.
- These are slides of the talk given at IEEE International Conference on Software Testing Verification and Validation Workshop, ICSTW 2022.
Climate Impact of Software Testing at Nordic Testing Days
My slides at Nordic Testing Days 6.6.2024
Climate impact / sustainability of software testing discussed on the talk. ICT and testing must carry their part of global responsibility to help with the climat warming. We can minimize the carbon footprint but we can also have a carbon handprint, a positive impact on the climate. Quality characteristics can be added with sustainability, and then measured continuously. Test environments can be used less, and in smaller scale and on demand. Test techniques can be used in optimizing or minimizing number of tests. Test automation can be used to speed up testing.
Driving Business Innovation: Latest Generative AI Advancements & Success Story
Are you ready to revolutionize how you handle data? Join us for a webinar where we’ll bring you up to speed with the latest advancements in Generative AI technology and discover how leveraging FME with tools from giants like Google Gemini, Amazon, and Microsoft OpenAI can supercharge your workflow efficiency.
During the hour, we’ll take you through:
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!
UiPath Test Automation using UiPath Test Suite series, part 6
Welcome to UiPath Test Automation using UiPath Test Suite series part 6. In this session, we will cover Test Automation with generative AI and Open AI.
UiPath Test Automation with generative AI and Open AI webinar offers an in-depth exploration of leveraging cutting-edge technologies for test automation within the UiPath platform. Attendees will delve into the integration of generative AI, a test automation solution, with Open AI advanced natural language processing capabilities.
Throughout the session, participants will discover how this synergy empowers testers to automate repetitive tasks, enhance testing accuracy, and expedite the software testing life cycle. Topics covered include the seamless integration process, practical use cases, and the benefits of harnessing AI-driven automation for UiPath testing initiatives. By attending this webinar, testers, and automation professionals can gain valuable insights into harnessing the power of AI to optimize their test automation workflows within the UiPath ecosystem, ultimately driving efficiency and quality in software development processes.
What will you get from this session?
1. Insights into integrating generative AI.
2. Understanding how this integration enhances test automation within the UiPath platform
3. Practical demonstrations
4. Exploration of real-world use cases illustrating the benefits of AI-driven test automation for UiPath
Topics covered:
What is generative AI
Test Automation with generative AI and Open AI.
UiPath integration with generative AI
Speaker:
Deepak Rai, Automation Practice Lead, Boundaryless Group and UiPath MVP
Let's Integrate MuleSoft RPA, COMPOSER, APM with AWS IDP along with Slack
Discover the seamless integration of RPA (Robotic Process Automation), COMPOSER, and APM with AWS IDP enhanced with Slack notifications. Explore how these technologies converge to streamline workflows, optimize performance, and ensure secure access, all while leveraging the power of AWS IDP and real-time communication via Slack notifications.
GraphRAG for Life Science to increase LLM accuracy
GraphRAG for life science domain, where you retriever information from biomedical knowledge graphs using LLMs to increase the accuracy and performance of generated answers
How to Get CNIC Information System with Paksim Ga.pptx
Pakdata Cf is a groundbreaking system designed to streamline and facilitate access to CNIC information. This innovative platform leverages advanced technology to provide users with efficient and secure access to their CNIC details.
Pushing the limits of ePRTC: 100ns holdover for 100 days
At WSTS 2024, Alon Stern explored the topic of parametric holdover and explained how recent research findings can be implemented in real-world PNT networks to achieve 100 nanoseconds of accuracy for up to 100 days.
Recently uploaded (20)
Observability Concepts EVERY Developer Should Know -- DeveloperWeek Europe.pdf
Observability Concepts EVERY Developer Should Know -- DeveloperWeek Europe.pdf
Presentation of the OECD Artificial Intelligence Review of Germany
Presentation of the OECD Artificial Intelligence Review of Germany
Full-RAG: A modern architecture for hyper-personalization
Full-RAG: A modern architecture for hyper-personalization
AI 101: An Introduction to the Basics and Impact of Artificial Intelligence
AI 101: An Introduction to the Basics and Impact of Artificial Intelligence
Best 20 SEO Techniques To Improve Website Visibility In SERP
Best 20 SEO Techniques To Improve Website Visibility In SERP
Cosa hanno in comune un mattoncino Lego e la backdoor XZ?
Cosa hanno in comune un mattoncino Lego e la backdoor XZ?
20240609 QFM020 Irresponsible AI Reading List May 2024
20240609 QFM020 Irresponsible AI Reading List May 2024
HCL Notes and Domino License Cost Reduction in the World of DLAU
HCL Notes and Domino License Cost Reduction in the World of DLAU
GraphSummit Singapore | The Future of Agility: Supercharging Digital Transfor...
GraphSummit Singapore | The Future of Agility: Supercharging Digital Transfor...
Climate Impact of Software Testing at Nordic Testing Days
Climate Impact of Software Testing at Nordic Testing Days
Driving Business Innovation: Latest Generative AI Advancements & Success Story
Driving Business Innovation: Latest Generative AI Advancements & Success Story
UiPath Test Automation using UiPath Test Suite series, part 6
UiPath Test Automation using UiPath Test Suite series, part 6
Let's Integrate MuleSoft RPA, COMPOSER, APM with AWS IDP along with Slack
Let's Integrate MuleSoft RPA, COMPOSER, APM with AWS IDP along with Slack
GraphRAG for Life Science to increase LLM accuracy
GraphRAG for Life Science to increase LLM accuracy
How to Get CNIC Information System with Paksim Ga.pptx
How to Get CNIC Information System with Paksim Ga.pptx
Pushing the limits of ePRTC: 100ns holdover for 100 days
Pushing the limits of ePRTC: 100ns holdover for 100 days
LLM project deployment plan
- 1. LLM Pilot Programme Nancy Baker Chief Operating Officer, Global Security Intelligence [email_address]