This week, we begin by spotlighting Turing's test, a crucial concept in computer science. It sparks discussions about how AI emulates human intelligence, ultimately elevating productivity and creativity. A recent Hardvard study revealed how AI improves worker productivity and reduces task completion time by 25% while also improving quality by 40%. A study with 758 Boston Consulting Group consultants revealed that GPT-4 boosted productivity by 12.2% on tasks it could handle.
Writer’s Credit: Special shout-out to Vidhu Jain for their valuable contribution to this week’s newsletter content!
Cheers,
Merlyn Shelley
Editor-in-Chief, Packt
⚡ TechWave: AI/GPT News & Analysis
OpenAI Expands to EU with Dublin Office and Key Hires: The ChatGPT creator is opening its first European Union office in Dublin, signaling its readiness for upcoming AI regulatory challenges. This move follows OpenAI's announcement of its third office, with locations in San Francisco and London. The expansion into Ireland is strategically significant, as many tech companies choose it as a hub to engage with European regulators and clients while benefiting from favorable tax rates. OpenAI is actively hiring for positions in Dublin, including an associate general counsel, policy and partnerships lead, privacy program manager, software engineer focused on privacy, and a media relations lead. This expansion highlights OpenAI's commitment to addressing privacy concerns, especially in the EU, where ChatGPT faced scrutiny and regulatory actions related to data protection.
AI-Powered Stable Audio Transforms Text into High-Quality Music: Stability AI has unveiled Stable Audio, an AI model capable of converting text descriptions into stereo 44.1 kHz music and sound effects. This breakthrough technology raises the potential of AI-generated audio rivaling human-made compositions. Stability AI collaborated with AudioSparx, incorporating over 800,000 audio files and text metadata into the model, enabling it to mimic specific sounds based on text commands. Stable Audio operates efficiently, rendering 95 seconds of 16-bit stereo audio at 44.1 kHz in under a second using Nvidia A100 GPUs. It comes with free and Pro plans, offering users the ability to generate music with varying lengths and quantities, marking a significant advancement in AI-generated audio quality.
Oracle Introduces AI-Powered Clinical Digital Assistant for Healthcare: Oracle has unveiled its AI-powered Clinical Digital Assistant to enhance electronic health record (EHR) solutions in healthcare. This innovation aims to automate administrative tasks for caregivers, allowing them to focus on patient care. It addresses concerns related to the adoption of generative AI technologies in healthcare. The assistant offers multimodal support, responding to both text and voice commands, streamlining tasks such as accessing patient data and prescriptions. It remains active during appointments, providing relevant information and suggesting actions. Patients can also interact with it for appointment scheduling and medical queries. Oracle plans a full rollout of capabilities over the next year.
Generative AI to Dominate Game Development in 5-10 Years, Says Bain Study: A study by global consulting firm Bain & Company predicts that generative AI will account for more than 50% of game development in the next 5 to 10 years, up from less than 5% currently. The research surveyed 25 gaming executives worldwide, revealing that most believe generative AI will enhance game quality and expedite development, but only 20% think it will reduce costs. Additionally, 60% don't expect generative AI to significantly alleviate the talent shortage in the gaming industry, emphasizing the importance of human creativity. The study highlights that generative AI should complement human creativity rather than replace it.
Google DeepMind's AI Program, AlphaMissense, Predicts Harmful DNA Mutations:Researchers at Google DeepMind have developed AlphaMissense, an artificial intelligence program that can predict whether genetic mutations are harmless or likely to cause diseases, with a focus on missense mutations, where a single letter is misspelled in the DNA code. AlphaMissense assessed 71 million single-letter mutations affecting human proteins, determining 57% were likely harmless, 32% likely harmful, and uncertain about the rest. The program's predictions have been made available to geneticists and clinicians to aid research and diagnosis. AlphaMissense performs better than current programs, potentially helping identify disease-causing mutations and guiding treatment.
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If Splunk is a part of your professional toolkit, consider exploring the Splunk 9.x Enterprise Certified Admin Guide. In an era where the IT sector's demand for Splunk expertise is consistently increasing, this resource proves invaluable. It comprehensively addresses essential aspects of Splunk Enterprise, encompassing installation, license management, user and forwarder administration, index creation, configuration file setup, data input handling, field extraction, and beyond. Moreover, the inclusion of self-assessment questions facilitates a thorough understanding, rendering it an indispensable guide for Splunk Enterprise administrators aiming to excel in their field. Interested in getting a sneak peek of Chapter 1 without any commitment? Simply click the button below to access it.
Understanding the Prompt Lifecycle: A Comprehensive Guide: A step-by-step guide to the prompt lifecycle, which is crucial for effective prompt engineering in AI applications. The guide covers four main stages: Design & Experiment, Differentiate & Personalize, Serve & Operate, and Analyze Feedback & Adapt. In each stage, you'll learn how to design, differentiate, serve, and adapt prompts effectively, along with the specific tools required. Additionally, the post addresses the current state of tooling solutions for prompt lifecycle management and highlights the existing gaps in prompt engineering tooling.
Exploring LLM Selection and Evaluation: A Comprehensive Guide: In this post, you'll discover a comprehensive guide to selecting and evaluating LLMs. The guide delves into the intricate process of choosing the right LLM for your specific task and provides valuable insights into evaluating their performance effectively. By reading this post, you can expect to gain a thorough understanding of the criteria for LLM selection, the importance of evaluation metrics, and practical tips to make informed decisions when working with these powerful language models.
A Primer on 3D Gaussian Splatting: Rasterization and Its Future in Graphics: In this post, you'll delve into the world of 3D Gaussian Splatting, a rasterization technique with promising implications for graphics. You'll explore the core concept of 3D Gaussian Splatting, which involves representing scenes using gaussians instead of triangles. The post guides you through the entire process, from Structure from Motion (SfM) to converting points to gaussians and training the model for optimal results. It also touches on the importance of differentiable Gaussian rasterization.
How to Build a Multi-GPU System for Deep Learning in 2023: A Step-by-Step Guide: Learn how to construct a multi-GPU system tailored for deep learning while staying within budget constraints. The guide begins by delving into crucial GPU considerations, emphasizing the importance of VRAM, performance (evaluated via FLOPS and tensor cores), slot width, and power consumption. It offers practical advice on choosing the right GPU for your budget. The post then moves on to selecting a compatible motherboard and CPU, paying special attention to PCIe lanes and slot spacing. The guide also covers RAM, disk space, power supply, and PC case considerations, offering insights into building an efficient multi-GPU system.
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This week’s featured article is written by Ben Auffarth, the Head of Data Science at loveholidays.
LangChain provides an intuitive framework that makes it easier for AI developers, data scientists, and even those new to NLP technology to create applications using LLMs.
What can I build with LangChain?
LangChain empowers various NLP use cases such as virtual assistants, content generation models for summaries or translations, question answering systems, and more. It has been used to solve a variety of real-world problems.
For example, LangChain has been used to build chatbots, question answering systems, and data analysis tools. It has also been used in a number of different domains, including healthcare, finance, and education.
You can build a wide variety of applications with LangChain, including:
Chatbots: It can be used to build chatbots that can interact with users in a natural way.
Question answering: LangChain can be used to build question answering systems that can answer questions about a variety of topics.
Data analysis: You can use it for automated data analysis and visualization to extract insights.
Code generation: You can set up software pair programming assistants that can help to solve business problems.
If you're intrigued by this, we invite you to join us at our upcoming virtual conference for an in-depth exploration of LangChain and gain a better understanding of how to responsibly apply Large Language Models (LLMs) and move beyond merely producing statistically driven responses.
The author will then take you on the practical journey of crafting your own chatbot, akin to the capabilities of ChatGPT.
Missed the Early Bird Special offer for the big event? No worries! You can still save 40% by booking your seat now.
Learn How to Orchestrate Ray-Based ML Workflows with Amazon SageMaker Pipelines: Discover the benefits of combining Ray and Amazon SageMaker for distributed ML in this comprehensive guide. Understand how Ray, an open-source distributed computing framework, simplifies distributed ML tasks, and how SageMaker seamlessly integrates with it. This post provides a step-by-step tutorial on building and deploying a scalable ML workflow using these tools, covering data ingestion, data preprocessing with Ray Dataset, model training, hyperparameter tuning with XGBoost-Ray, and more. You'll also explore how to orchestrate these steps using SageMaker Pipelines, enabling efficient and automated ML workflows. Dive into the detailed code snippets and unleash the potential of your ML projects.
Building and Deploying Tool-Using LLM Agents with AWS SageMaker JumpStart Foundation Models: Discover how to create and deploy LLM agents with extended capabilities, including access to external tools and self-directed task execution. This post introduces LLM agents and guides you through building and deploying an e-commerce LLM agent using Amazon SageMaker JumpStart and AWS Lambda. This agent leverages tools to enhance its functionality, such as answering queries about returns and order updates. The architecture involves a Flan-UL2 model deployed as a SageMaker endpoint, data retrieval tools with AWS Lambda, and integration with Amazon Lex for use as a chatbot.
Step-by-Step Guide to Text Generation with GPT using Hugging Face Transformers Library in Python: In this post, you'll learn how to utilize the Hugging Face Transformers library for text generation and natural language processing without the need for OpenAI API keys. The Hugging Face Transformers library offers a range of models, including GPT-2, GPT-3, GPT-4, T5, BERT, and more, each with unique characteristics and use cases. You'll explore how to install the required libraries, choose a pretrained language model, and generate text based on a prompt or context using Python and the Flask framework. This comprehensive guide will enable you to implement text generation applications with ease, making AI-powered interactions accessible to users.
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ise-uiuc/Repilot: Patch generation tool designed for Java and based on large language models and code completion engines.
turboderp/exllamav2: Early release of an inference library for local LLMs on consumer GPUs, requiring further testing and development.
liuyuan-pal/SyncDreamer: Focuses on creating multiview-consistent images from single-view images.
FL33TW00D/whisper-turbo: Fast, cross-platform Whisper implementation running in your browser or electron app offering real-time streaming and privacy.
OpenBMB/ChatDev: Virtual software company run by intelligent agents with various roles aiming to revolutionize programming and study collective intelligence.
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