This is part 1 of a talk on Transformers. Transformers are a deep learning architecture that has been used in NLP. They are now been used in the famous ChatGPT model (InstructGPT).
Build an LLM-powered application using LangChain.pdfAnastasiaSteele10
LangChain is an advanced framework that allows developers to create language model-powered applications. It provides a set of tools, components, and interfaces that make building LLM-based applications easier. With LangChain, managing interactions with language models, chaining together various components, and integrating resources like APIs and databases is a breeze. The platform includes a set of APIs that can be integrated into applications, allowing developers to add language processing capabilities without having to start from scratch.
Transformer modality is an established architecture in natural language processing that utilizes a framework of self-attention with a deep learning approach.
This presentation was delivered under the mentorship of Mr. Mukunthan Tharmakulasingam (University of Surrey, UK), as a part of the ScholarX program from Sustainable Education Foundation.
GPT and other Text Transformers: Black Swans and Stochastic ParrotsKonstantin Savenkov
Over the last year, we see increasingly more performant Text Transformers models, such as GPT-3 from OpenAI, Turing from Microsoft, and T5 from Google. They are capable of transforming the text in very creative and unexpected ways, like generating a summary of an article, explaining complex concepts in a simple language, or synthesizing realistic datasets for AI training. Unlike more traditional Machine Learning models, they do not require vast training datasets and can start based on just a few examples.
In this talk, we will make a short overview of such models, share the first experimental results and ask questions about the future of the content creation process. Are those models ready for prime time? What will happen to the professional content creators? Will they be able to compete against such powerful models? Will we see GPT post-editing similar to MT post-editing? We will share some answers we have based on the extensive experimenting and the first production projects that employ this new technology.
Fine tune and deploy Hugging Face NLP modelsOVHcloud
Are you currently managing AI projects that require a lot of GPU power?
Are you tired of managing the complexity of your infrastructures, GPU instances and your Kubeflow yourself?
Need flexibility for your AI platform or SaaS solution?
OVHcloud innovates in AI by offering simple and turnkey solutions to train your models and put them into production.
A presentation on Bidirectional Encoder Representations from Transformers (BERT) meant to introduce the model's use cases and training mechanism. Best viewed with powerpoint since it contain many slide animations.
Build an LLM-powered application using LangChain.pdfAnastasiaSteele10
LangChain is an advanced framework that allows developers to create language model-powered applications. It provides a set of tools, components, and interfaces that make building LLM-based applications easier. With LangChain, managing interactions with language models, chaining together various components, and integrating resources like APIs and databases is a breeze. The platform includes a set of APIs that can be integrated into applications, allowing developers to add language processing capabilities without having to start from scratch.
Transformer modality is an established architecture in natural language processing that utilizes a framework of self-attention with a deep learning approach.
This presentation was delivered under the mentorship of Mr. Mukunthan Tharmakulasingam (University of Surrey, UK), as a part of the ScholarX program from Sustainable Education Foundation.
GPT and other Text Transformers: Black Swans and Stochastic ParrotsKonstantin Savenkov
Over the last year, we see increasingly more performant Text Transformers models, such as GPT-3 from OpenAI, Turing from Microsoft, and T5 from Google. They are capable of transforming the text in very creative and unexpected ways, like generating a summary of an article, explaining complex concepts in a simple language, or synthesizing realistic datasets for AI training. Unlike more traditional Machine Learning models, they do not require vast training datasets and can start based on just a few examples.
In this talk, we will make a short overview of such models, share the first experimental results and ask questions about the future of the content creation process. Are those models ready for prime time? What will happen to the professional content creators? Will they be able to compete against such powerful models? Will we see GPT post-editing similar to MT post-editing? We will share some answers we have based on the extensive experimenting and the first production projects that employ this new technology.
Fine tune and deploy Hugging Face NLP modelsOVHcloud
Are you currently managing AI projects that require a lot of GPU power?
Are you tired of managing the complexity of your infrastructures, GPU instances and your Kubeflow yourself?
Need flexibility for your AI platform or SaaS solution?
OVHcloud innovates in AI by offering simple and turnkey solutions to train your models and put them into production.
A presentation on Bidirectional Encoder Representations from Transformers (BERT) meant to introduce the model's use cases and training mechanism. Best viewed with powerpoint since it contain many slide animations.
How does ChatGPT work: an Information Retrieval perspectiveSease
In this talk, we will explore the underlying mechanisms of ChatGPT, a large-scale language model developed by OpenAI, from the perspective of Information Retrieval (IR). We will delve into the process of training the model using massive amounts of data, the techniques used to optimize the model’s performance, and how the IR concepts such as tokenization, vectorization, and ranking are used in generating responses. We will also discuss how ChatGPT handles contextual understanding and how it leverages the power of transfer learning to generate high-quality and relevant responses. Software engineers will gain insights into how a modern conversational AI system like ChatGPT works, providing a better understanding of its strengths and limitations, and how to best integrate it into their software applications.
This abstract has been fully written by ChatGPT with the simple prompt in input <Write an abstract for a talk called “How does ChatGPT work? An Information Retrieval perspective”, the audience is software engineers>.
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 the Transformers architecture and BERTSuman Debnath
The transformer is one of the most popular state-of-the-art deep (SOTA) learning architectures that is mostly used for natural language processing (NLP) tasks. Ever since the advent of the transformer, it has replaced RNN and LSTM for various tasks. The transformer also created a major breakthrough in the field of NLP and also paved the way for new revolutionary architectures such as BERT.
Deep dive into LangChain integration with Neo4j.pptxTomazBratanic1
Deep dive into LangChain integrations with Neo4j. Learn how to query your graph with LangChain either by generating Cypher statements using LLMs or using the vector index.
And then there were ... Large Language ModelsLeon Dohmen
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.
Large Language Models, No-Code, and Responsible AI - Trends in Applied NLP in...David Talby
An April 2023 presentation to the AMIA working group on natural language processing. The talk focuses on three current trends in NLP and how they apply in healthcare: Large language models, No-code, and Responsible AI.
Bert version three for Chinese lanuage. bert is a bert bert bert bert bert bergt bert bert bert bertbert bert bet bertb Bert version three for Chinese lanuage. bert is a bert bert bert bert bert bergt bert bert bert bertbert bert bet bertb Bert version three for Chinese lanuage. bert is a bert bert bert bert bert bergt bert bert bert bertbert bert bet bertb Bert version three for Chinese lanuage. bert is a bert bert bert bert bert bergt bert bert bert bertbert bert bet bertb Bert version three for Chinese lanuage. bert is a bert bert bert bert bert bergt bert bert bert bertbert bert bet bertb Bert version three for Chinese lanuage. bert is a bert bert bert bert bert bergt bert bert bert bertbert bert bet bertb Bert version three for Chinese lanuage. bert is a bert bert bert bert bert bergt bert bert bert bertbert bert bet bertb Bert version three for Chinese lanuage. bert is a bert bert bert bert bert bergt bert bert bert bertbert bert bet bertb Bert version three for Chinese lanuage. bert is a bert bert bert bert bert bergt bert bert bert bertbert bert bet bertb Bert version three for Chinese lanuage. bert is a bert bert bert bert bert bergt bert bert bert bertbert bert bet bertb Bert version three for Chinese lanuage. bert is a bert bert bert bert bert bergt bert bert bert bertbert bert bet bertb
BERT: Bidirectional Encoder Representation from Transformer.
BERT is a Pretrained Model by Google for State of the art NLP tasks.
BERT has the ability to take into account Syntaxtic and Semantic meaning of Text.
Over the last two years, the field of Natural Language Processing (NLP) has witnessed the emergence of transfer learning methods and architectures which significantly improved upon the state-of-the-art on pretty much every NLP tasks.
The wide availability and ease of integration of these transfer learning models are strong indicators that these methods will become a common tool in the NLP landscape as well as a major research direction.
In this talk, I'll present a quick overview of modern transfer learning methods in NLP and review examples and case studies on how these models can be integrated and adapted in downstream NLP tasks, focusing on open-source solutions.
Website: https://fwdays.com/event/data-science-fwdays-2019/review/transfer-learning-in-nlp
Dive into the world of GPT-4, the state-of-the-art AI language model by OpenAI. Learn how to craft effective prompts and unlock the full potential of GPT-4 for a wide range of applications, including content generation.
Keywords:
GPT-4, OpenAI, artificial intelligence, language model, prompting, content generation, machine learning, natural language processing, NLP, deep learning, tokenization, context window, prompt engineering, reinforcement learning, fine-tuning, response quality, API, zero-shot learning, few-shot learning, AI ethics, use cases, best practices, performance optimization, transformer architecture, AI-powered solutions.
This talk overviews my background as a female data scientist, introduces many types of generative AI, discusses potential use cases, highlights the need for representation in generative AI, and showcases a few tools that currently exist.
Breaking down the AI magic of ChatGPT: A technologist's lens to its powerful ...rahul_net
ChatGPT has taken the world of natural language processing by storm, and as an experienced AI practitioner, enterprise architect, and technologist with over two decades of experience, I'm excited to share my insights on how this innovative powerhouse is designed from an AI components perspective. In this post, I'll provide a fresh take on the key components that make ChatGPT a powerful conversational AI tool, including its use of the Transformer architecture, pre-training on large amounts of text data, and fine-tuning with human feedback. With ChatGPT's massive success, there's no doubt that it's changing the way we think about language and conversation. So, whether you're a seasoned pro or new to the world of AI, my post will provide a valuable perspective on this fascinating technology. Check out my slides to learn more!
How does ChatGPT work: an Information Retrieval perspectiveSease
In this talk, we will explore the underlying mechanisms of ChatGPT, a large-scale language model developed by OpenAI, from the perspective of Information Retrieval (IR). We will delve into the process of training the model using massive amounts of data, the techniques used to optimize the model’s performance, and how the IR concepts such as tokenization, vectorization, and ranking are used in generating responses. We will also discuss how ChatGPT handles contextual understanding and how it leverages the power of transfer learning to generate high-quality and relevant responses. Software engineers will gain insights into how a modern conversational AI system like ChatGPT works, providing a better understanding of its strengths and limitations, and how to best integrate it into their software applications.
This abstract has been fully written by ChatGPT with the simple prompt in input <Write an abstract for a talk called “How does ChatGPT work? An Information Retrieval perspective”, the audience is software engineers>.
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 the Transformers architecture and BERTSuman Debnath
The transformer is one of the most popular state-of-the-art deep (SOTA) learning architectures that is mostly used for natural language processing (NLP) tasks. Ever since the advent of the transformer, it has replaced RNN and LSTM for various tasks. The transformer also created a major breakthrough in the field of NLP and also paved the way for new revolutionary architectures such as BERT.
Deep dive into LangChain integration with Neo4j.pptxTomazBratanic1
Deep dive into LangChain integrations with Neo4j. Learn how to query your graph with LangChain either by generating Cypher statements using LLMs or using the vector index.
And then there were ... Large Language ModelsLeon Dohmen
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.
Large Language Models, No-Code, and Responsible AI - Trends in Applied NLP in...David Talby
An April 2023 presentation to the AMIA working group on natural language processing. The talk focuses on three current trends in NLP and how they apply in healthcare: Large language models, No-code, and Responsible AI.
Bert version three for Chinese lanuage. bert is a bert bert bert bert bert bergt bert bert bert bertbert bert bet bertb Bert version three for Chinese lanuage. bert is a bert bert bert bert bert bergt bert bert bert bertbert bert bet bertb Bert version three for Chinese lanuage. bert is a bert bert bert bert bert bergt bert bert bert bertbert bert bet bertb Bert version three for Chinese lanuage. bert is a bert bert bert bert bert bergt bert bert bert bertbert bert bet bertb Bert version three for Chinese lanuage. bert is a bert bert bert bert bert bergt bert bert bert bertbert bert bet bertb Bert version three for Chinese lanuage. bert is a bert bert bert bert bert bergt bert bert bert bertbert bert bet bertb Bert version three for Chinese lanuage. bert is a bert bert bert bert bert bergt bert bert bert bertbert bert bet bertb Bert version three for Chinese lanuage. bert is a bert bert bert bert bert bergt bert bert bert bertbert bert bet bertb Bert version three for Chinese lanuage. bert is a bert bert bert bert bert bergt bert bert bert bertbert bert bet bertb Bert version three for Chinese lanuage. bert is a bert bert bert bert bert bergt bert bert bert bertbert bert bet bertb Bert version three for Chinese lanuage. bert is a bert bert bert bert bert bergt bert bert bert bertbert bert bet bertb
BERT: Bidirectional Encoder Representation from Transformer.
BERT is a Pretrained Model by Google for State of the art NLP tasks.
BERT has the ability to take into account Syntaxtic and Semantic meaning of Text.
Over the last two years, the field of Natural Language Processing (NLP) has witnessed the emergence of transfer learning methods and architectures which significantly improved upon the state-of-the-art on pretty much every NLP tasks.
The wide availability and ease of integration of these transfer learning models are strong indicators that these methods will become a common tool in the NLP landscape as well as a major research direction.
In this talk, I'll present a quick overview of modern transfer learning methods in NLP and review examples and case studies on how these models can be integrated and adapted in downstream NLP tasks, focusing on open-source solutions.
Website: https://fwdays.com/event/data-science-fwdays-2019/review/transfer-learning-in-nlp
Dive into the world of GPT-4, the state-of-the-art AI language model by OpenAI. Learn how to craft effective prompts and unlock the full potential of GPT-4 for a wide range of applications, including content generation.
Keywords:
GPT-4, OpenAI, artificial intelligence, language model, prompting, content generation, machine learning, natural language processing, NLP, deep learning, tokenization, context window, prompt engineering, reinforcement learning, fine-tuning, response quality, API, zero-shot learning, few-shot learning, AI ethics, use cases, best practices, performance optimization, transformer architecture, AI-powered solutions.
This talk overviews my background as a female data scientist, introduces many types of generative AI, discusses potential use cases, highlights the need for representation in generative AI, and showcases a few tools that currently exist.
Breaking down the AI magic of ChatGPT: A technologist's lens to its powerful ...rahul_net
ChatGPT has taken the world of natural language processing by storm, and as an experienced AI practitioner, enterprise architect, and technologist with over two decades of experience, I'm excited to share my insights on how this innovative powerhouse is designed from an AI components perspective. In this post, I'll provide a fresh take on the key components that make ChatGPT a powerful conversational AI tool, including its use of the Transformer architecture, pre-training on large amounts of text data, and fine-tuning with human feedback. With ChatGPT's massive success, there's no doubt that it's changing the way we think about language and conversation. So, whether you're a seasoned pro or new to the world of AI, my post will provide a valuable perspective on this fascinating technology. Check out my slides to learn more!
As an AI language model, ChatGPT is a program consisting of a large neural network that has been trained on vast amounts of textual data. Specifically, ChatGPT is a variant of the GPT (Generative Pre-trained Transformer) family of models developed by OpenAI.
In the rapidly evolving landscape of artificial intelligence, ChatGPT stands as a beacon of innovation, continuously pushing the boundaries of what's possible in natural language understanding. As we peer into the future, it's evident that ChatGPT is poised to become an even more integral part of our daily lives, reshaping how we communicate, learn, and interact with technology.
One of the most exciting prospects for the future of ChatGPT is its potential to become even more contextually aware and emotionally intelligent. Imagine a ChatGPT that not only comprehends the words we type but also discerns the underlying emotions and intentions behind them. This heightened level of understanding could revolutionize customer service interactions, therapy sessions, and even personal conversations, fostering deeper connections and empathy in the digital realm.In the rapidly evolving landscape of artificial intelligence, ChatGPT stands as a beacon of innovation, continuously pushing the boundaries of what's possible in natural language understanding. As we peer into the future, it's evident that ChatGPT is poised to become an even more integral part of our daily lives, reshaping how we communicate, learn, and interact with technology.
One of the most exciting prospects for the future of ChatGPT is its potential to become even more contextually aware and emotionally intelligent. Imagine a ChatGPT that not only comprehends the words we type but also discerns the underlying emotions and intentions behind them. This heightened level of understanding could revolutionize customer service interactions, therapy sessions, and even personal conversations, fostering deeper connections and empathy in the digital realm.In the rapidly evolving landscape of artificial intelligence, ChatGPT stands as a beacon of innovation, continuously pushing the boundaries of what's possible in natural language understanding. As we peer into the future, it's evident that ChatGPT is poised to become an even more integral part of our daily lives, reshaping how we communicate, learn, and interact with technology.
One of the most exciting prospects for the future of ChatGPT is its potential to become even more contextually aware and emotionally intelligent. Imagine a ChatGPT that not only comprehends the words we type but also discerns the underlying emotions and intentions behind them. This heightened level of understanding could revolutionize customer service interactions, therapy sessions, and even personal conversations, fostering deeper connections and empathy in the digital realm
.https://www.pnytrainings.com/
ICEIT'20 Cython for Speeding-up Genetic AlgorithmAhmed Gad
The presentation of the paper titled "Cython for Speeding-up Genetic Algorithm". Find it at IEEE Explore: https://ieeexplore.ieee.org/document/9113210
The abstract of the paper:
This paper proposes a library for implementing the genetic algorithm using Python mainly in NumPy and speeding-up its execution using Cython. The preliminary Python implementation is inspected for possible optimizations. The 4 main changes include statically defining data types for the NumPy arrays, specifying the data type of the array elements in addition to the number of dimensions, using indexing for looping through the arrays, and finally disabling some unnecessary features in Cython. Using Cython, the NumPy array processing is 1250 times faster than CPython. The Cythonized version of the genetic algorithm is 18 times faster than the Python version.
The GPT-3 model architecture is a transformer-based neural network that has been fed 45TB of text data. It is non-deterministic, in the sense that given the same input, multiple runs of the engine will return different responses. Also, it is trained on massive datasets that covered the entire web and contained 500B tokens, humongous 175 Billion parameters, a more than 100x increase over GPT-2, which was considered state-of-the-art technology with 1.5 billion parameters.
Everything You wanted to Know About Distributed TracingAmuhinda Hungai
In the age of microservices, understanding how applications are executing in a highly distributed environment can be complicated. Looking at log files only gives a snapshot of the whole story and looking at a single service in isolation simply does not give enough information. Each service is just one side of a bigger story. Distributed tracing has emerged as an invaluable technique that succeeds in summarizing all sides of the story into a shared timeline. Yet deploying it can be quite challenging, especially in the large scale, polyglot environments of modern companies that mix together many different technologies. During this session, we will take a look at patterns and means to implement Tracing for services. After introducing the basic concepts we will cover how the tracing model works, and how to safely use it in production to troubleshoot and diagnose issues.
As Europe's leading economic powerhouse and the fourth-largest hashtag#economy globally, Germany stands at the forefront of innovation and industrial might. Renowned for its precision engineering and high-tech sectors, Germany's economic structure is heavily supported by a robust service industry, accounting for approximately 68% of its GDP. This economic clout and strategic geopolitical stance position Germany as a focal point in the global cyber threat landscape.
In the face of escalating global tensions, particularly those emanating from geopolitical disputes with nations like hashtag#Russia and hashtag#China, hashtag#Germany has witnessed a significant uptick in targeted cyber operations. Our analysis indicates a marked increase in hashtag#cyberattack sophistication aimed at critical infrastructure and key industrial sectors. These attacks range from ransomware campaigns to hashtag#AdvancedPersistentThreats (hashtag#APTs), threatening national security and business integrity.
🔑 Key findings include:
🔍 Increased frequency and complexity of cyber threats.
🔍 Escalation of state-sponsored and criminally motivated cyber operations.
🔍 Active dark web exchanges of malicious tools and tactics.
Our comprehensive report delves into these challenges, using a blend of open-source and proprietary data collection techniques. By monitoring activity on critical networks and analyzing attack patterns, our team provides a detailed overview of the threats facing German entities.
This report aims to equip stakeholders across public and private sectors with the knowledge to enhance their defensive strategies, reduce exposure to cyber risks, and reinforce Germany's resilience against cyber threats.
Levelwise PageRank with Loop-Based Dead End Handling Strategy : SHORT REPORT ...Subhajit Sahu
Abstract — Levelwise PageRank is an alternative method of PageRank computation which decomposes the input graph into a directed acyclic block-graph of strongly connected components, and processes them in topological order, one level at a time. This enables calculation for ranks in a distributed fashion without per-iteration communication, unlike the standard method where all vertices are processed in each iteration. It however comes with a precondition of the absence of dead ends in the input graph. Here, the native non-distributed performance of Levelwise PageRank was compared against Monolithic PageRank on a CPU as well as a GPU. To ensure a fair comparison, Monolithic PageRank was also performed on a graph where vertices were split by components. Results indicate that Levelwise PageRank is about as fast as Monolithic PageRank on the CPU, but quite a bit slower on the GPU. Slowdown on the GPU is likely caused by a large submission of small workloads, and expected to be non-issue when the computation is performed on massive graphs.
StarCompliance is a leading firm specializing in the recovery of stolen cryptocurrency. Our comprehensive services are designed to assist individuals and organizations in navigating the complex process of fraud reporting, investigation, and fund recovery. We combine cutting-edge technology with expert legal support to provide a robust solution for victims of crypto theft.
Our Services Include:
Reporting to Tracking Authorities:
We immediately notify all relevant centralized exchanges (CEX), decentralized exchanges (DEX), and wallet providers about the stolen cryptocurrency. This ensures that the stolen assets are flagged as scam transactions, making it impossible for the thief to use them.
Assistance with Filing Police Reports:
We guide you through the process of filing a valid police report. Our support team provides detailed instructions on which police department to contact and helps you complete the necessary paperwork within the critical 72-hour window.
Launching the Refund Process:
Our team of experienced lawyers can initiate lawsuits on your behalf and represent you in various jurisdictions around the world. They work diligently to recover your stolen funds and ensure that justice is served.
At StarCompliance, we understand the urgency and stress involved in dealing with cryptocurrency theft. Our dedicated team works quickly and efficiently to provide you with the support and expertise needed to recover your assets. Trust us to be your partner in navigating the complexities of the crypto world and safeguarding your investments.
Opendatabay - Open Data Marketplace.pptxOpendatabay
Opendatabay.com unlocks the power of data for everyone. Open Data Marketplace fosters a collaborative hub for data enthusiasts to explore, share, and contribute to a vast collection of datasets.
First ever open hub for data enthusiasts to collaborate and innovate. A platform to explore, share, and contribute to a vast collection of datasets. Through robust quality control and innovative technologies like blockchain verification, opendatabay ensures the authenticity and reliability of datasets, empowering users to make data-driven decisions with confidence. Leverage cutting-edge AI technologies to enhance the data exploration, analysis, and discovery experience.
From intelligent search and recommendations to automated data productisation and quotation, Opendatabay AI-driven features streamline the data workflow. Finding the data you need shouldn't be a complex. Opendatabay simplifies the data acquisition process with an intuitive interface and robust search tools. Effortlessly explore, discover, and access the data you need, allowing you to focus on extracting valuable insights. Opendatabay breaks new ground with a dedicated, AI-generated, synthetic datasets.
Leverage these privacy-preserving datasets for training and testing AI models without compromising sensitive information. Opendatabay prioritizes transparency by providing detailed metadata, provenance information, and usage guidelines for each dataset, ensuring users have a comprehensive understanding of the data they're working with. By leveraging a powerful combination of distributed ledger technology and rigorous third-party audits Opendatabay ensures the authenticity and reliability of every dataset. Security is at the core of Opendatabay. Marketplace implements stringent security measures, including encryption, access controls, and regular vulnerability assessments, to safeguard your data and protect your privacy.
Innovative Methods in Media and Communication Research by Sebastian Kubitschk...
Transformers - Part 1
1. Transformers - Part 1
Dr. Akshika Wijesundara
The science behind ChatGPT
Research Associate King's College London | Consultant at National
University of Singapore
2. Topics
● OpenAI and ChatGPT
● “Attention is all you need”
● RNNs vs Transformers
● Self-Attention
● Transformer architecture
● Ethical implications and challenges
3. OpenAI is an AI research and deployment company with the
mission to ensure that artificial general intelligence benefits all of
humanity.
6. How is ChatGPT built?
● GPT (Generative Pre-trained Transformer) - 3 is an autoregressive language model (175B
parameters).
● Later InstructGPT was developed to address the shortcomings of GPT3.
● InstructGPT uses human feedback to reinforce the model (1.3B parameters)
7.
8. Transformers > RNN*
RNN Transformers
Process a sequence of data in parallel
😕 😃
Handle long-term dependencies
😐 😃
Capturing global dependencies
😐 😃
Self-attention
😕 😃
22. Ethical & Legal Implications
● Misuse
○ Fake news and bots that spread it
○ Using the tool in exams
● Biases
● Impact on human intelligence
● Copyright infringement
23. What we covered
● Overview of ChatGPT
● Transformers
● Self-Attention
● Ethical implications of ChatGPT