Archive 30.07.2024

Inspired by the paper-folding art of origami, engineers have discovered a way to make a single plastic cubed structure transform into more than 1,000 configurations using only three active motors.

Researchers have developed a self-powered 'bug' that can skim across the water, and they hope it will revolutionize aquatic robotics.

Researchers at Binghamton University, State University of New York have developed a self-powered "bug" that can skim across the water, and they hope it will revolutionize aquatic robotics.

Generative AI is a rapidly evolving field with a plethora of fascinating applications, from creating realistic images and videos to generating human-like text and beyond. As the technology advances, the demand for skilled professionals who can harness the power of generative AI is growing exponentially. However, navigating the myriad of tutorials and courses available can be overwhelming, especially when trying to acquire these critical skills quickly.

To help you on your journey, we have curated a list of some of the highest-quality courses from respected providers such as DeepLearning.ai, Google Cloud, AWS, IBM, and more. These courses are designed with a strong practical focus, ensuring that you gain real-world skills needed to build applications powered by large language models (LLMs). The best part? Most of these courses are available for free, making it easier than ever to dive into the world of generative AI.

In this article, we provide an overview of these top courses, highlighting their key features and content to help you find the best fit for your learning needs. Whether you’re a beginner just starting out or an advanced developer looking to deepen your expertise, there’s something here for everyone.

Here are the courses we cover:

1. Generative AI for Everyone by DeepLearning.ai
2. Introduction to Generative AI by Google Cloud
3. Generative AI: Introduction and Applications by IBM
4. ChatGPT Promt Engineering for Developers by OpenAI and DeepLearning.ai
5. LangChain for LLM Application Development by LangChain and DeepLearning.ai
6. LangChain: Chat with Your Data by LangChain and DeepLearning.ai
7. Open Source Models with Hugging Face by Hugging Face and DeepLearning.ai
8. Building LLM Powered Apps by Weights & Biases
9. Generative AI with Large Language Models by AWS and DeepLearning.ai
10. LLM University by Cohere
11. Amazon Bedrock & AWS Generative AI by AWS
12. Finetuning Large Language Models by Lamini and DeepLearning.ai
13. Reinforcement Learning from Human Feedback by Google Cloud and DeepLearning.ai
14. Generative AI for Software Development by DeepLearning.ai
15. Generative AI for Developers by Google Cloud

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Top Generative AI Courses with Practical Focus

Now let’s have an overview of some of the top generative AI courses available today. These courses are designed to equip you with practical skills and knowledge to excel in the field of generative AI.

1. Generative AI for Everyone by DeepLearning.ai

Level: Beginner

Duration: 3 hours

Cost: Free

Instructor: Andrew Ng, founder of DeepLearning.ai, co-founder of Google Brain and Coursera

Audience: This course is tailored for anyone keen on understanding the applications, impacts, and foundational technologies of generative AI. No prior coding skills or AI knowledge are required, making it accessible to a broad audience.

Content:

• Introduction to Generative AI: An overview of what generative AI is and its capabilities.
• Applications and Limitations: Insights into what generative AI can and cannot do, helping learners set realistic expectations.
• Practical Uses: Guidance on integrating generative AI into various personal or business contexts.
• Debunking Myths: Addressing common misconceptions about generative AI and promoting a clear understanding.
• Best Practices: Strategies for effective learning and evaluating the potential usefulness of generative AI in different scenarios.

This concise yet comprehensive course offers a foundational understanding of generative AI, making it an excellent starting point for anyone looking to delve into this transformative technology.

2. Introduction to Generative AI by Google Cloud

Level: Beginner

Duration: Specialization with 4 courses (approximately 4 hours total)

Cost: Free

Instructor: Google Cloud Training Team

Audience: This course is ideal for individuals looking to deepen their understanding of generative AI and large language models. While it is beginner-friendly, a basic grasp of AI concepts will help learners fully absorb the material.

Content:

• Generative AI Fundamentals: Defining generative AI and explaining its underlying mechanisms.
• Applications of Generative AI: Exploring various real-world applications and use cases of generative AI.
• Large Language Models: Defining LLMs, their functionalities, and practical use cases.
• Prompt Tuning: An overview of prompt tuning and its significance in optimizing AI outputs.
• Google’s Gen AI Development Tools: Insight into the tools provided by Google for developing generative AI applications.
• Responsible AI Practices: Discussion on responsible AI practices and how Google implements its AI Principles to ensure ethical AI development.

While the course does have a notable focus on Google’s AI practices and tools, it remains a robust introduction to generative AI and LLMs, providing valuable knowledge and insights for anyone interested in the field.

3. Generative AI: Introduction and Applications by IBM

Level: Beginner

Duration: 6 hours

Cost: Free

Instructor: Rav Ahuja, Chief Curriculum Officer and Global Program Director at IBM Skills Network

Audience: This course is perfect for those seeking to understand generative AI with a strong emphasis on practical applications and real-world use cases. It is well-suited for individuals interested in learning about generative AI models and tools across various media formats, including text, code, image, audio, and video.

Content:

• Generative vs. Discriminative AI: Understanding the fundamental differences between generative and discriminative AI.
• Capabilities and Use Cases: Insight into the abilities of generative AI and its practical applications in the real world.
• Sector-Specific Applications: Exploration of how generative AI is applied across different industries and sectors.
• Generative AI Models and Tools: Detailed examination of common generative AI models and tools used for generating text, code, images, audio, and video.

This comprehensive course provides a broad understanding of generative AI, emphasizing its real-world applications and diverse use cases, making it an excellent resource for beginners aiming to grasp the practical aspects of this technology.

4. ChatGPT Promt Engineering for Developers by OpenAI and DeepLearning.ai

Level: Beginner

Duration: 1 hour

Cost: Free

Instructors: Isa Fulford, Member of Technical Staff at OpenAI, and Andrew Ng, founder of DeepLearning.ai, co-founder of Google Brain and Coursera

Audience: This course is designed for developers who are beginning to build applications based on large language models. Basic Python coding skills are recommended to fully benefit from the course content.

Content:

• Introduction into LLMs: An overview of how large language models work.
• Best Practices for Prompt Engineering: Guidance on creating effective prompts for various tasks.
• Using LLM APIs: Practical examples of using LLM APIs in applications for tasks such as:
  • Summarizing: Condensing user reviews for brevity.
  • Inferring: Performing sentiment classification and topic extraction.
  • Transforming Text: Executing tasks like translation, spelling, and grammar correction.
  • Expanding Text: Automatically generating content such as emails.
• Effective Prompt Writing: Two key principles for writing effective prompts and systematic approaches to engineering good prompts.
• Building a Custom Chatbot: Step-by-step instructions on building a custom chatbot.
• Hands-on Experience: Numerous examples and interactive exercises in a Jupyter notebook environment to practice prompt engineering.

This succinct course provides developers with the essential skills and knowledge to harness the power of LLMs in their applications, emphasizing practical examples and hands-on experience to ensure a solid understanding of prompt engineering.

5. LangChain for LLM Application Development by LangChain and DeepLearning.ai

Level: Beginner

Duration: 1 hour

Cost: Free

Instructors: Harrison Chase, co-founder and CEO at LangChain, and Andrew Ng, founder of DeepLearning.ai, co-founder of Google Brain and Coursera

Audience: This beginner-friendly course is designed for developers who want to learn how to expand the use cases and capabilities of language models in application development using the LangChain framework. Basic Python knowledge is recommended to maximize the course benefits.

Content:

• Models, Prompts, and Parsers: Learn how to call LLMs, provide effective prompts, and parse the responses.
• Memories for LLMs: Understand how to use memories to store conversations and manage limited context space, enhancing the functionality of your applications.
• Chains: Create sequences of operations to build more complex workflows and capabilities within your applications.
• Question Answering over Documents: Apply LLMs to your proprietary data and specific use case requirements, making your applications more versatile and powerful.
• Agents: Explore the emerging development of LLMs as reasoning agents, opening up new possibilities for advanced application functionalities.

This concise course equips developers with the skills to significantly expand the use cases and capabilities of language models using the LangChain framework, enabling the creation of robust and sophisticated applications in a short amount of time.

6. LangChain: Chat with Your Data by LangChain and DeepLearning.ai

Level: Beginner

Duration: 1 hour

Cost: Free

Instructor: Harrison Chase, co-founder and CEO at LangChain

Audience: This course is aimed at developers who want to learn how to build practical applications that interact with data using LangChain and LLMs. Developers should be familiar with Python.

Content:

• Retrieval Augmented Generation (RAG): Learn how to retrieve contextual documents from external datasets.
• Chatbot Development: Build a chatbot that answers questions based on your documents.
• Document Loading: Explore over 80 loaders to access various data sources, including audio and video.
• Document Splitting: Understand best practices for data splitting.
• Vector Stores and Embeddings: Discover embeddings and vector store integrations in LangChain.
• Advanced Retrieval: Master techniques for accessing and indexing data to retrieve relevant information.
• Question Answering: Create a one-pass question-answering solution.

This concise course provides developers with the skills to effectively use language models and LangChain, enabling the creation of powerful applications using their own data.

7. Open Source Models with Hugging Face by Hugging Face and DeepLearning.ai

Level: Beginner

Duration: 1 hour

Cost: Free

Instructors: Maria Khalusova, Marc Sun, and Younes Belkada from the Hugging Face technical team

Audience: This course is for anyone looking to quickly and easily build AI applications using open-source models.

Content:

• Model Selection: Choose open-source models from the Hugging Face Hub for NLP, audio, image, and multimodal tasks.
• Transformers Library: Learn to use the transformers library to create a chatbot capable of multi-turn conversations.
• NLP Tasks: Translate between languages, summarize documents, and measure text similarity for search and retrieval.
• Audio Tasks: Convert audio to text with Automatic Speech Recognition (ASR) and text to audio with Text-to-Speech (TTS).
• Multimodal Tasks: Generate audio narrations for images by combining object detection and text-to-speech models.

This course provides the essential building blocks to combine into pipelines, enabling you to develop AI-enabled applications using Hugging Face’s open-source models.

8. Building LLM-Powered Apps by Weights & Biases

Level: Intermediate

Duration: 2 hours of video content

Cost: Free

Instructors: Shreya Rajpal, creator of Guardrails AI; Anton Troynikov, co-founder of Chroma; Shahram Anver, co-creator of Rebuff

Audience: This course is designed for developers looking to build LLM applications. Intermediate Python experience is required, but no prior machine learning skills are needed.

Content:

• Fundamentals of AI-Powered Applications: Learn the basics of APIs, chains, and prompt engineering for building AI applications.
• Hands-On Application Development: Follow a step-by-step guide to build your own app, using a support automation bot for a software company as an example.
• Enhancing Your LLM App: Discover methods for improving your LLM-powered app through experimentation and evaluation.

This course equips developers with the necessary skills to create and optimize LLM applications, providing practical insights and hands-on experience.

9. Generative AI with Large Language Models by AWS and DeepLearning.ai

Level: Intermediate

Duration: 16 hours

Cost: Free

Instructors: Chris Fregly and Shelbee Eigenbrode, Principal Solutions Architects for Generative AI at Amazon Web Services (AWS), Antje Barth, Principal Developer Advocate for Generative AI at AWS, and Mike Chambers, Developer Advocate for Generative AI at AWS.

Audience: This course is for developers who want to understand the fundamentals of generative AI and how to deploy it in real-world applications. Intermediate Python coding skills and a basic understanding of machine learning concepts, such as supervised and unsupervised learning, loss functions, and data splitting, are required.

Content:

• Generative AI Lifecycle: Learn the key steps in a typical LLM-based generative AI lifecycle, from data gathering and model selection to performance evaluation and deployment.
• Transformer Architecture: Gain a detailed understanding of the transformer architecture powering LLMs, including their training process and how fine-tuning adapts them to specific use cases.
• Empirical Scaling Laws: Optimize the model’s objective function by balancing dataset size, compute budget, and inference requirements using empirical scaling laws.
• Advanced Techniques: Apply state-of-the-art methods for training, tuning, inference, and deployment to maximize model performance within project constraints.
• Business Implications: Explore the challenges and opportunities generative AI presents for businesses through insights from industry researchers and practitioners.

This comprehensive course provides developers with the knowledge and tools to effectively deploy generative AI in real-world applications, emphasizing practical techniques and industry insights.

10. LLM University by Cohere

Level: Intermediate to Advanced

Duration: 8 modules consisting of 42 articles, with content available in both video and text formats

Cost: Free

Instructors: Cohere team

Audience: This course is designed for developers and technical professionals who want to quickly and efficiently start building LLM applications.

Content:

• Key Concepts of Large Language Models: Gain a deep understanding of the fundamental concepts behind LLMs.
• Text Representation and Generation: Learn the principles of text representation and how LLMs generate text.
• Deployment: Discover how to deploy LLM applications using various tools.
• Semantic Search: Explore how semantic search works.
• Prompt Engineering: Understand the techniques of prompt engineering.
• Retrieval-Augmented Generation (RAG): Learn how to implement RAG in your applications.
• Tool Use: Get hands-on experience with various tools essential for LLM development.

This comprehensive course provides a thorough grounding in both basic and advanced concepts, enabling developers to understand the inner workings of LLMs and build sophisticated applications.

11. Amazon Bedrock & AWS Generative AI by AWS 

Level: Beginner to Advanced

Duration: 11 hours

Cost: $19.99

Instructor: Rahul Trisal, AWS Community Builder in the Serverless Category and Senior AWS Architect with over 15 years of experience in AWS Cloud Strategy, Architecture, and Migration

Audience: This course is aimed at developers who want to build LLM applications using AWS infrastructure. Basic AWS knowledge is recommended, but the course includes a refresher on Python, AWS Lambda, and API Gateway for those who need it.

Content:

• Introduction to AI/ML: Basic overview of AI/ML concepts.
• Generative AI Fundamentals: Learn how generative AI works and explore foundation models in depth.
• Amazon Bedrock: Detailed console walkthrough, architecture, pricing, and inference parameters.
• Use Cases: Seven practical applications including design, text summarization, chatbots, code generation, and more.
• GenAI Project Lifecycle: Comprehensive guide on defining use cases, choosing a foundation model, prompt engineering, and fine-tuning models.

This course provides a thorough introduction to building LLM applications on AWS, covering both foundational concepts and practical implementations to equip developers with the necessary skills and knowledge.

12. Finetuning Large Language Models by Lamini and DeepLearning.ai

Level: Intermediate

Duration: 1 hour

Cost: Free

Instructor: Sharon Zhou, Co-Founder and CEO of Lamini

Audience: This course is designed for learners who want to understand the techniques and applications of finetuning large language models. Familiarity with Python and a deep learning framework such as PyTorch is recommended.

Content:

• Application of Finetuning: Learn when and why to apply finetuning on LLMs.
• Data Preparation: Understand how to prepare your data for finetuning.
• Training and Evaluation: Gain hands-on experience training and evaluating an LLM on your data.

Upon completion, learners will be equipped with the skills to effectively finetune LLMs, enhancing their ability to tailor models to specific applications and datasets.

13. Reinforcement Learning from Human Feedback by Google Cloud and DeepLearning.ai

Level: Intermediate

Duration: 1 hour

Cost: Free

Instructor: Nikita Namjoshi, Developer Advocate at Google Cloud

Audience: This course is for anyone with intermediate Python knowledge interested in learning about using the Reinforcement Learning from Human Feedback (RLHF) technique.

Content:

• Conceptual Understanding of RLHF: Gain insights into the RLHF training process.
• Datasets Exploration: Learn about the “preference” and “prompt” datasets used in RLHF training.
• Practical Application: Use the open-source Google Cloud Pipeline Components Library to fine-tune the Llama 2 model with RLHF.
• Model Assessment: Compare the tuned LLM against the original base model by evaluating loss curves and using the “Side-by-Side (SxS)” method.

This course equips learners with the conceptual and practical skills needed to apply RLHF for tuning LLMs, enhancing their understanding and capabilities in this advanced technique.

14. Generative AI for Software Development by DeepLearning.ai

Level: Intermediate

Duration: 3 courses (around 15 hours), starting on Sep 25, 2024

Cost: Free

Instructor: Laurence Moroney, Chief AI Scientist at VisionWorks Studios and former AI lead at Google

Audience: This course is designed for software developers who want to explore how to use LLMs to improve their efficiency and optimize their code quality.

Content:

• Understanding LLMs: Learn how large language models work to effectively leverage them in your development process.
• Pair-Coding with LLMs: Modify data structures for production and handle big data scales efficiently with the assistance of an LLM.
• Software Testing with LLMs: Use LLMs to identify bugs, create edge case tests, and update code to correct errors, enhancing your software testing processes.
• Database Implementation and Design: Build a local database from scratch and partner with an LLM to optimize software design for efficient and secure data access.

This comprehensive course equips software developers with the knowledge and skills to integrate LLMs into their workflow, enhancing productivity and code quality.

15. Generative AI for Developers by Google Cloud

Level: Intermediate to Advanced

Duration: 11 courses (about 19 hours in total)

Cost: Free

Instructor: Google Cloud team

Audience: This Generative AI Learning Path is tailored for App Developers, Machine Learning Engineers, and Data Scientists. It’s recommended to complete the Introduction to Generative AI learning path before starting this course.

Content:

• Generative AI Applications: Explore various applications, including image generation, image captioning, and text generation.
• Gen AI Model Architectures: Dive deep into model architectures such as the attention mechanism, encoder-decoder architecture, and transformer models.
• Vertex AI Studio: Learn how to use Vertex AI Studio for developing and deploying generative AI models.
• Responsible AI for Developers: Understand the principles of responsible AI and how to implement them in your projects.
• Machine Learning Operations (MLOps) for Generative AI: Gain insights into MLOps practices tailored for generative AI workflows.

Although the course emphasizes Google Cloud infrastructure and practices, it offers a comprehensive understanding of how generative AI works and how to apply these models in real-world scenarios.

Elevate Your Development Skills with Generative AI Courses

As generative AI continues to revolutionize the tech landscape, developers must equip themselves with the latest skills to stay competitive. The courses outlined in this article provide targeted, practical training in generative AI, helping you build sophisticated LLM-powered applications. Featuring instruction from esteemed providers such as DeepLearning.ai, Google Cloud, AWS, and IBM, these courses ensure you gain the expertise needed to thrive in this fast-evolving field.

Whether you’re a beginner ready to start your journey or an experienced developer seeking to enhance your capabilities, these courses offer a clear pathway to mastering generative AI. Embrace these learning opportunities and take your development skills to the next level with confidence and competence.

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The post Accelerate Your AI Skills: Essential Generative AI Courses for Developers appeared first on TOPBOTS.

Inspired by the paper-folding art of origami, North Carolina State University engineers have discovered a way to make a single plastic cubed structure transform into more than 1,000 configurations using only three active motors. The findings could pave the way for shape-shifting artificial systems that can take on multiple functions and even carry a load—like versatile robotic structures used in space, for example.

ChatGPT-Maker Releases New Bargain Version

OpenAI has released a new chatbot that’s almost as good as its flagship AI engine — ChatGPT 4o — and much cheaper to run.

Dubbed “ChatGPT 4o Mini,” the new AI engine is free-to-use on a limited basis to anyone visiting the ChatGPT Web site.

ChatGPT 4o Mini is expected to be a hit with developers looking to build AI applications atop the AI engine, which OpenAI says costs 60% less to run.

An important note: While ChatGPT 4o Mini is less advanced as the OpenAI flagship version, it’s still plenty smart.

ChatGPT 4o Mini, for example, beats-out the original AI software that powered ChatGPT to world fame and frenzy in late 2022, according to OpenAI test reports.

In other news and analysis on AI writing:

*In-Depth Guide: 10 Best AI SEO Tools: Writers looking for a nice round-up of AI-powered tools specializing in search engine optimization may want to check-out this piece.

The guide offers a short-and-sweet summary of ten AI-powered SEO tools that writer Antoine Tardif considers tops.

Observes Tardif: “By leveraging these technologies, you can streamline your SEO efforts, produce high-quality content and improve your website’s visibility and user experience.”

*The MVP of AI Chatbots?: Facebook Founder Takes Another Swing for the Fences: Longtime AI evangelist Mark Zuckerberg has updated his challenge to ChatGPT, dubbed, Llama 3.1.

Observes writer Anuj Mudaliar: “While both models (AI engines) are thought to exhibit excellent performance in natural language processing, Llama 3.1’s relatively smaller parameter size may limit its ability to complete complex tasks, as GPT-4 works on 1.76 trillion parameters.

“However, practical performance is yet to be measured by users on a wide scale.”

*Très magnifique?: French AI Startup Says It’s Built a Better ChatGPT: French AI startup Mistral is out with its own competitor to ChatGPT, which it says matches — and sometimes exceeds — the market leader’s performance.

For example: Mistral’s ability to auto-generate accurate computer code is actually better than the most robust version of ChatGPT — ChatGPT 4o — according to the company.

Dubbed Mistral Large 2, the new AI engine is available on Google Vertex AI, Azure AI Studio, Amazon Bedrock and IBM watsonx.ai.

*Scribblers Rejoice!: Microsoft Promising to Transform Chicken Scratch Into Digital Gold: Users of MS Copilot in OneNote may soon have access to a tool that enables input into OneNote via handwritten stylus.

The overall goal is for MS Copilot to ingest the handwritten notes and then enable users to auto-generate written summaries, ask questions of the data they’ve entered and auto-generate to-do lists based on the notes.

Currently, the new tool is in beta testing.

*Can We Talk?: When Study Data Becomes a Conversationalist: Research software firm Recollective is out with a new AI tool that offers conversational access to qualitative research.

Observes Alfred Jay, CEO, Recollective: “Our new AI features are designed to complement and enhance the way researchers work, enabling them to focus on what truly matters: extracting actionable insights and creating compelling narratives.”

Specifically, researchers can pose targeted questions to the study data they’ve gathered and engage in a dialog with the research to unveil insights and trends they may have otherwise missed.

*Humanizey AI Hawks Solution to Bot-Babble: Writers looking for a more ‘human feel’ from writing auto-generated by AI may want to give AI Humanizer a test-drive.

The tool is designed to auto-rewrite text produced by AI chatbots so that it sounds more human.

Plus, the resulting, re-written text also should bypass detection as ‘AI generated’ when assessed by AI writing detectors such as GPTZero, Turnitin and Originality AI, according to David Holand, CEO, Humanizey AI.

*Another AI News Anchor Pops-Up: Because Humans Are So Yesterday: Add South Korean cable TV channel MBN to the growing list of news outlets using AI-powered news anchors to present the news.

This one is actually a knock-off of a human news anchor on the channel — Kim Ju-ha — and is programmed to look exactly like Ju-ha and mimic the female news anchor mannerisms.

Observes the AI bot, dubbed Al Kim: “I was created through deep learning 10 hours of video of Kim Ju-ha, learning the details of her voice, the way she talks, facial expressions, the way her lips move, and the way she moves her body.

“I am able to report news exactly the way that anchor Kim Ju-ha would.”

*Going for Google’s Jugular: ChatGPT-Maker Tinkers With New Search Engine: OpenAI is currently testing an AI-powered search engine it hopes will unseat Google as the King of Search.

Observes writer Deepa Seetharaman: “The tool, called SearchGPT, will summarize the information found on Web sites, including news sites and let users ask follow-up questions — just as they can currently with OpenAI’s popular chatbot, ChatGPT.

“SearchGPT is OpenAI’s most direct challenge yet to Google’s dominance in search since the release of ChatGPT in 2022 caught the tech company flat-footed.”

*Fast Times at AI High: New Startup Looking to Build ‘AI-First’ Schools: Former OpenAI researcher Andrej Karpathy is looking to redefine education by building new schools with AI at their core.

Karpathy describes his new venture, dubbed ‘Eureka Labs,’ as a “new kind of school that is AI native,” with the express aim of developing a “Teacher + AI symbiosis” that will allow “anyone to learn anything,” according to writer Andrew Tarantola.

Karpathy “envisions an education system built from the ground-up with AI as its core tenet — with human teachers developing lesson plans while being supplemented in the classroom by digital assistants,” Tarantola adds.

Share a Link:  Please consider sharing a link to https://RobotWritersAI.com from your blog, social media post, publication or emails. More links leading to RobotWritersAI.com helps everyone interested in AI-generated writing.

–Joe Dysart is editor of RobotWritersAI.com and a tech journalist with 20+ years experience. His work has appeared in 150+ publications, including The New York Times and the Financial Times of London.

The post Dumber, Cheaper appeared first on Robot Writers AI.

While interest in Siggraph as an event has declined over the years, the advent of generative AI and the near-term potential arrival of AGI (Artificial General Intelligence) should cause a significant resurgence. This is because AI dramatically changes how people […]

The post Siggraph 2024: Learning About the Present and Future of Generative AI and the Coming of AGI appeared first on TechSpective.

Scientists have identified an automatic behavior in flies that helps them assess wind conditions -- its presence and direction -- before deploying a strategy to follow a scent to its source. The fact that they can do this is surprising -- can you tell if there's a gentle breeze if you stick your head out of a moving car? Flies aren't just reacting to an odor with a preprogrammed response: they are responding in context-appropriate manner. This knowledge potentially could be applied to train more sophisticated algorithms for scent-detecting drones to find the source of chemical leaks.

Researchers create a storybook generation system for personalized vocabulary learning.

A team of computer scientists and roboticists with members from Texas A&M University in the U.S., and the Mohamed Bin Zayed University of Artificial Intelligence in Abu Dhabi, working with a colleague from Boston Dynamics, has configured a robot made by Boston Dynamics to seek out and stun weeds using a small blowtorch. The team has posted a paper describing their efforts to the arXiv preprint server.

A Guide To Custom AI Solutions: How To Use ChatGPT For Sales?

What is ChatGPT?

ChaGPT Chat Generative Pre-trained Transformer) a boom in the technology industry introduced by OpenAI in 2022. It’s a profound innovation of cutting-edge Artificial Intelligence (AI) technology. OpenAI’s Large Language Model (LLM) powered ChatGPT has created waves in the modern tech industry.

ChatGPT is trained with a diverse set of databases which allows the application to generate creative, detailed, structured, and tweaked content responses. Delivering human-like text responses to user prompts, this modern generative AI application is gaining momentum across the industry. Moreover, with its Natural Language Processing capabilities, ChatGPT can better understand and engage customers users through a qualitative conversation.

Generating content as a core application, ChatGPT is also witnessing breakneck growth in various aspects. Using ChatGPT a software development team can write code and test code and a marketing and sales team can create compelling email content and sales campaign content faster. Further, integration of ChatGPT’s APIs into your CRM-like applications could help you instantly respond to customer queries and ensure personalized experience through reliable communication all the time. Hence, companies can achieve customer satisfaction and improve retention rates.

Like these, the applications of ChatGPT or the uses of ChatGPT are incredible. The HR department, development team, operational team, marketing, and sales department can avail the benefits of ChatGPT. Especially, the use of ChatGPT for sales and marketing increasing nowadays to streamline various aspects of the sales processes.

Today, in this article, we would like to give you a little information on how can ChatGPT be useful for sales and what are the benefits of customizing ChatGPT for your sales operations.

 

Top Applications of ChatGPT For Sales

• ChatGPT For Customer Support

The generative AI powered ChatGPT using Natural Language Processing potentialities would help sales and marketing teams to automate responses to customer queries. Hence, integrating a well-trained GPT model into CRM applications will help can automate the process of receiving customer queries and sending accurate responses faster than a human workforce does. IT will improve the customer loyalty and at the same time boost productivity.

• Lead Campaign Content Ideas

Leveraging the innovative advanced ChatGPT platform, sales and marketing professionals can generate content required for digital campaigns. ChatGPT is been trained with vast versatile databases related to market trends that help sales professionals get content ideas and relevant snippets and other marketing materials for boosting their campaign activities.

• ChatGPT Makes Language Translations Easier   

ChatGPT is the most useful asset for translating languages. Using ChatGPT like large language learning model, it will be easy to sales professionals to give prompts in one language and getting responses in required language. Hence it can be used as a language translator and supports multilingual interactions.

• Customer Segregation Content 

Giving necessary customer data input as a prompt to this advanced and AI-powered GenAI-based ChatGPT, sales professionals can segregate customers’ data based on their requirements, order types, order quantity, payment status, etc. It will reduce manual efforts and help in maintaining clear and structured sales data with zero errors.

• For Email Generation

In this digital world, getting noticed by prospects is a key step for ensuring a strong lead pipeline and improving conversions. Giving introductions to the brand’s services and products and doing continuous follow-ups are two mandatory tasks of a sales professional. ChatGPT will play a significant role in email generation in just a matter of seconds.

Providing your requirements such as targeted audience group, email intention, and email type (a service introductory draft or a follow-up), sales professionals can get creative email content. Later, it can be customized as per business requirements. Hence, time-consuming email writeups would be automated and help resources focus more on lead generation and nurturing.

• Data Summarizations     

It is one of the top benefits of ChatGPT in sales. ChatGPT helps the sales team or operations team to better manage sales processes and derive insights from historic sales data. These insights or summarized data would help the sales team to predict the market growth opportunities and create results-driven sales strategies.

• Generate and Nurture Leads

Integrating ChatGPT into your existing sales applications and processes, identification of quality leads, gathering associated customer data, and creating lead generation striation would become seamless. By defining your prospects, ChatGPT assists in picking the best quality leads seamlessly and contributes to optimized ROI.

• Guidance on communication strategies

ChatGPT guides communication strategies to sales representatives. You can also train ChatGPT to automate onboarding processes, pushing automated recommendations to leads based on their previous search history feedback collection and analysis, and many more can be done by customizing ChatGPT APIs and integrating them into your sales applications.

These are a few significant applications of ChatGPT in sales. This powerful Generative AI application helps the sales team generate content that meets their needs. Like these, ChatGPT offers multiple benefits to sales teams.

 

Wrapping Up

Whether conversational AI or generative AI apps will have a bright scope in the years ahead with their smart, intelligent, and automation capabilities. Marketing, sales, development, and almost every department can gain from ChatGPT content generation potentialities and improve their focus on core activities.

USM is the best AI app development company in the USA. Specializing in the design, development, and deployment of trending AI, and ML. NLP, RPA, and other leading-edge technology-based mobile apps, USM is the best partner for all types of software development projects. Based on your AI project requirements and scope, our expert AI consultants provide you with top-notch AI consulting services and AI development services that enable intelligent automation across your business processes.

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Artificial intelligence (AI) is hot right now. Also hot: the data centers that power the technology. And keeping those centers cool requires a tremendous amount of energy. The problem is only going to grow as high-powered AI-based computers and devices become commonplace. That's why researchers are devising a new type of cooling system that promises to dramatically reduce energy demands.

One of the locations where RODE adds value is for DHL eCommerce in Rotterdam. In this machine, two Ensenso 3D cameras from IDS Imaging Development Systems GmbH are implemented to provide the required image data.

A new type of valve that makes soft robots more resilient to damage, has been developed by engineers at the University of Sheffield.

Breakthrough models AlphaProof and AlphaGeometry 2 solve advanced reasoning problems in mathematics