Towards AI

APRIL 10, 2023

Photo by Unsplash.com The launch of ChatGPT has sparked significant interest in generative AI, and people are becoming more familiar with the ins and outs of large language models. It’s worth noting that prompt engineering plays a critical role in the success of training such models. Some examples of prompts include: 1.

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ODSC - Open Data Science

JANUARY 29, 2024

The role of prompt engineer has attracted massive interest ever since Business Insider released an article last spring titled “ AI ‘Prompt Engineer Jobs: $375k Salary, No Tech Backgrund Required.” It turns out that the role of a Prompt Engineer is not simply typing questions into a prompt window.

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Marktechpost

APRIL 1, 2024

Ever since its inception, ChatGPT has taken the world by storm, marking the beginning of the era of generative AI. Although large language models (LLMs) had been developed prior to the launch of ChatGPT, the latter’s ease of accessibility and user-friendly interface took the adoption of LLM to a new level.

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Unite.AI

SEPTEMBER 15, 2023

While many are familiar with ChatGPT's prowess as a conversational AI, its true potential extends far beyond standard interactions. As we delve deeper into the concept of ChatGPT personas, it's essential to appreciate this foundational flexibility, which allows for the creation of highly specialized and tailored AI identities.

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Artificial Corner

NOVEMBER 16, 2023

Remember that annual subscribers on my Substack can redeem up to 2 of my Udemy courses for free (ChatGPT, Python, data science, or my best-selling web scraping course). Prompt engineering is a must-have skill that any AI enthusiast should have … at least until OpenAI released GPTs and DALL-E 3. They’re just prompts.

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Unite.AI

OCTOBER 5, 2023

One of the AI's shining stars is ChatGPT, a conversational model developed by OpenAI. Its core capability lies in generating human-like text based on the prompts it receives. From casual conversations to in-depth technical explanations, ChatGPT can engage with an array of topics, making it a sought-after resource.

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Towards AI

APRIL 12, 2024

Fine-Tuning AI Responses with Savvy Prompt Engineering I don’t know about you, but as much as I love ChatGPT, specifically GPT 4, one thing I cannot stand is the tone in which it writes, and its habit of inundating me with reams of text when I ask a basic question. Join thousands of data leaders on the AI newsletter.

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Marktechpost

APRIL 28, 2024

The course also teaches how to use tools and models like ChatGPT, GitHub CoPilot, Google Gemini, and IBM Watson Code Assistant. It also covers topics like generative AI and its applications, as well as prompt engineering. AI For Everyone “AI For Everyone” has been designed by DeepLearning.AI

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Unite.AI

JULY 26, 2023

Since its launch, ChatGPT has been making waves in the AI sphere, attracting over 100 million users in record time. The secret sauce to ChatGPT's impressive performance and versatility lies in an art subtly nestled within its programming – prompt engineering. This makes us all prompt engineers to a certain degree.

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Unite.AI

DECEMBER 22, 2023

Understanding Prompt Engineering Prompt engineering is the art and science of crafting inputs (prompts) to get desired outputs from AI models like ChatGPT. ChatGPT, built upon OpenAI's GPT-3 and GPT-4 architectures, has advanced significantly, becoming more responsive and context-aware.

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ODSC - Open Data Science

AUGUST 24, 2023

5 Jobs That Will Use Prompt Engineering in 2023 Whether you’re looking for a new career or to enhance your current path, these jobs that use prompt engineering will become desirable in 2023 and beyond. That’s why enriching your analysis with trusted, fit-for-use, third-party data is key to ensuring long-term success.

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Unite.AI

AUGUST 1, 2023

One such model that has garnered considerable attention is OpenAI's ChatGPT , a shining exemplar in the realm of Large Language Models. In the context of ChatGPT and OpenAI models, a prompt is the input that users provide to the models, usually in the form of text.

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AI News

NOVEMBER 15, 2023

The hype surrounding generative AI and the potential of large language models (LLMs), spearheaded by OpenAI’s ChatGPT, appeared at one stage to be practically insurmountable. As McLoone explains, it is all a question of purpose. “I Alongside being a general extension to ChatGPT, the Wolfram plugin can also synthesise code. “It

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Flipboard

AUGUST 3, 2023

Six months out from when it broke the internet, ChatGPT — and its numerous clones and adaptations — have drummed up great interest, and concerns, for teachers, school leaders and districts. Students and teachers in schools rich and poor will have access to these tools,” Stamford explains.

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AI News

MARCH 7, 2024

Anthropic, creators of Claude, released Claude 3 this week and claimed it to be a ‘new standard for intelligence’ , surging ahead of competitors such as ChatGPT and Google’s Gemini. The company says it has also achieved ‘near human’ proficiency in various tasks.

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Marktechpost

APRIL 16, 2024

It explains the fundamentals of LLMs and generative AI and also covers prompt engineering to improve performance. Developing Apps With GPT-4 and ChatGPT This book teaches how to create applications with large language models, such as text generation, Q&A, and content summarization tools.

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AI Weekly

SEPTEMBER 7, 2023

Neuroscientists Now Have a Checklist Recently I had what amounted to a therapy session with ChatGPT. plos.org ChatGPT vs Bing vs Bard vs Claude comparison which ones right for you? lesswrong.com Sponsor Things just got insanely easy for content creators Invideo AI will let you create publish-ready videos with just text prompts.

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Towards AI

FEBRUARY 15, 2023

Last Updated on February 15, 2023 by Editorial Team What happened this week in AI by Louis This week was rather chaotic in the world of large language models (LLMs) and “Generative AI” as large tech companies scrambled to display their technology in the wake of ChatGPT’s success. Hottest News 1.

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Towards AI

SEPTEMBER 22, 2023

In this new episode, the future human resistance sends a robot back in time to destroy OpenAI’s server farm, thereby preventing the emergence of ChatGPT and AGI. The birth of ChatGPT has caused a stir. One example is prompt engineering. Prompt engineering has proved to be very useful.

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Artificial Corner

JANUARY 25, 2024

What's cool about it is that it offers an interaction style similar to ChatGPT, but it's focused on coding. Here are some of my favorite commands: Diving deeper into the code: /explain Getting unstuck or fixing code snags: /fix Conducting tests on the code: /tests I have to say Copilot is one of my favorite tools. Subscribe now 5.

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Pickl AI

AUGUST 2, 2023

One such incredible innovation is ChatGPT, developed by OpenAI. ChatGPT is an AI language model that leverages the GPT-3.5 architecture to provide human-like responses to natural language prompts. However, a recent breakthrough came with the new version of ChatGPT, the GPT 4. What is ChatGPT? How to Use ChatGPT?

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Pickl AI

JULY 23, 2023

One effective technique is leveraging ChatGPT prompts, which can provide you with inspiration, guidance, and problem-solving assistance. In this article, we will explore ten ChatGPT prompts specifically tailored to boost productivity for programmers. Debugging Support- Debugging code can be challenging and time-consuming.

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ODSC - Open Data Science

AUGUST 14, 2023

I still don’t know what AI is” If you’re like my parents and think I work at ChatGPT, then you may have to learn a little bit more about AI. Funny enough, you can use AI to explain AI. Most AI-based programs have plenty of good tutorials that explain how to use the automation side of things as well.

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Viso.ai

FEBRUARY 21, 2024

The quality and performance of the LLM depend on the quality of the prompt it is given. Prompt engineering allows users to construct optimal prompts to improve the LLM response. This article will guide readers step by step through AI prompt engineering and discuss the following: What is a Prompt?

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Towards AI

MAY 12, 2023

The striking potential of LLMs has encouraged a lot of comparative research revolving around “humans vs. ChatGPT”. ChatGPT), and GPT 4 models and labelers from the Toloka crowdsourcing platform (Tolokers). We separated these characteristics in our experiment for better explainability. of it was used for testing.

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Flipboard

OCTOBER 28, 2023

Using ChatGPT to generate 4x more localized real estate content. Developing new AI-powered features across the company in areas like the home valuation process, including explaining home valuations to customers who ask how Redfin arrived at the number. Accepting around 25% of code suggestions from GitHub Copilot, increasing efficiency.

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Heartbeat

AUGUST 2, 2023

Large language models can be used for enormous language-related tasks like chatbots to have contextual conversations with a user base, summarize documents by deriving meaningful information from massive text, translation engines, and more. Addressing and mitigating biases in language models is an ongoing challenge.

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ODSC - Open Data Science

SEPTEMBER 20, 2023

We’re in an age where generative AI models like ChatGPT, Midjourney, and Google’s Bard are pushing the boundaries of what machines can do with human operators. So it’s no surprise that the ability to fine-tune prompts effectively has become a valuable skill. Leverage this pre-training by providing context in your prompts.

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Flipboard

MARCH 9, 2023

Prompts may well be the new oil. Writing the text strings that instruct AI systems like ChatGPT and DALL-E 2 to generate essays, articles, images and more has become a veritable profession, commanding salaries well into the six-figure range. Anyone can come up with prompts, of course. But only certain prompts (e.g.

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Flipboard

JUNE 13, 2023

Prompt: “A robot helping a software engineer develop code.” ” Generative AI is already changing the way software engineers do their jobs. Each of us leverage both Copilot and ChatGPT in day-to-day development, debugging, and learning.

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Artificial Corner

AUGUST 3, 2023

Prompt engineering in under 10 minutes — theory, examples and prompting on autopilot Master the science and art of communicating with AI. ChatGPT showed people what are the possibilities of NLP and AI in general. The tone, length, and complexity of the answer can be much different for two almost identical prompts.

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ODSC - Open Data Science

NOVEMBER 20, 2023

Prompt Optimization with GPT-4 and Langchain Mike Taylor | Owner | Saxifrage In this session, Mike Taylor discusses how you can use prompt engineering at scale — as part of a template, workflow, or product. HuggingFace models, Python, PyTorch, Jupyter Notebooks).

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Heartbeat

AUGUST 25, 2023

Introduction Prompt Engineering is arguably the most critical aspect in harnessing the power of Large Language Models (LLMs) like ChatGPT. However; current prompt engineering workflows are incredibly tedious and cumbersome. Logging prompts and their outputs to .csv First install the package via pip.

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Mlearning.ai

JANUARY 26, 2023

Paper Review: Constitutional AI, Training LLMs using Principles Governing the behavior of Generative AI through Principles The release of ChatGPT has taken the world by storm and competitors are trying to quickly develop and release their own similar models. Deepmind is aiming to release Sparrow towards the end of the year.

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Mlearning.ai

APRIL 15, 2023

Taking Google’s Generative AI Studio to a Test Drive The long expected competition to OpenAI’s chatGPT was clearly going to come from Google Cloud. The UI is less playful that chatGPT, however it allows access to the model parameters that can be tuned to achieve accurate results. Tuning the LLMs on your data can lead to cost reduction.

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Heartbeat

JANUARY 9, 2024

LLMs received a lot of media attention when ChatGPT was released in December 2022. We're committed to supporting and inspiring developers and engineers from all walks of life. LLMs have numerous uses, including product development, marketing, and customer service. We pay our contributors, and we don't sell ads.

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ODSC - Open Data Science

JANUARY 10, 2024

Takeaways include: The dangers of using post-hoc explainability methods as tools for decision-making, and where traditional ML falls short. I will also cover how smaller, domain-specific models can outperform general-purpose foundation models like ChatGPT on target use cases. What are the steps and core components behind these LLMs?

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