Hello, prompt engineers and AI enthusiasts!

We’ve been extra busy, including a great trip to Las Vegas for the AI4 Conference. And you’ve got another special issue with TWO episodes 🚀🚀

Episode 17 is from our days at the AI4 conference. It covers the rapid deployment of generative AI across industries, such as ChatAible for Enterprise Analytics and the revolutionary health startup, Vital Health. Plus, we'll delve into the world of education as we explore a cutting-edge coding tutor bot and its impact on learning. We also shine a spotlight on David Manley, a Harvard CS 50 professor, who has developed a custom coding tutor bot. Discover how this innovative tool adapts to each student's needs, helping them learn, reason, and solve coding problems independently. It's a brilliant example of the power of AI in education.

Episode 18 has Goda Go’s review of 432 AI writing tools. She shares in HTTA more information and you can Download the Full List for FREE. And we got a chance to sit down with Aaron Patzer and Felix Brann to go deeper into how Vital Health is using AI to simplify complex doctors' notes and aftercare instructions. Their helpful tool is breaking down medical jargon into easily digestible terms! It’s truly helping ensure that regular people are fully equipped to make informed decisions and communicate effectively with healthcare providers.

MidJourney Master Reference Guide

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Discord (Goda Go#3156 & Commordore_Wesmardo#2912)

Goda Go on Youtube: /@godago

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HTTTA Newsletter

1. Our work with BSD Education: helping Teachers use AI

e excited to share the Ultimate Guide to AI for Teachers. Since 2013 BSD Education has been helping teachers as a platform for virtual teaching and learning. They know the pain points that teachers often encounter when preparing virtual teaching plans. These usually are:

Time-Consuming Prep: Teachers frequently find themselves spending an excessive amount of time crafting lesson plans, which takes away from other essential tasks like interacting with students or professional development.

Resource Scarcity: Sourcing and organizing digital resources such as educational materials, videos, and interactive tools can be a daunting task, especially when they need to align with the curriculum.

Differentiation Challenges: Adapting lessons to cater to various learning styles and abilities in a virtual setting can be complex, requiring extensive planning and effort.

Assessment Complexity: Creating fair and effective assessments for remote learning, which provide insightful feedback to both students and teachers, is often a struggle.

Alignment with Standards: Ensuring that virtual lesson plans align with educational standards and learning objectives can be challenging and time-consuming.

Engagement and Personalization: Maintaining student engagement and personalizing instruction in an online environment requires innovative strategies and careful planning.

Repetitive Tasks: Managing routine administrative tasks, such as sending automated emails or tracking student progress, can eat into valuable teaching time.

Building this with BSD Education made us better appreciate the challenges educators face when developing virtual teaching plans and why solutions like AI-powered assistance can be a game-changer in simplifying their workloads.

2. The Gen AI that nails Text and helps people become more Creative

Recently launched - Ideogram.AI is quickly proving to be an excellent Midjourney alternative. There’s a lot of positive reviews out there and we believe this really democratizes Text to Image generation.

It’s a new image generation program available that actually handles text really well…For many people Midjourney, and Dall-e2, had a steep learning curve. Ideogram makes it simple to get started and produce some remarkable images from simple prompts! The Toronto based startup has already received $16.5 million USD in seed funding from 16z and others.

Ideogram's CEO, Mohammad Norouzi, brings a wealth of experience as a former senior staff research scientist at Google. Other founding members previously led AI projects at Google Brain, UC Berkeley, and the University of Toronto. Their launch statement shares their mission - “developing state-of-the-art AI tools that will make creative expression more accessible, fun, and efficient. We are pushing the limits of what’s possible with AI, with a focus on creativity and a high standard for trust and safety.”

We’ve played with the tool and highly recommend you check it out!

3. CS50 - Harvard’s Intro to Computer Science and why Everyone should Watch it

This is easily the most engaging, educational, informative, and well put together course there is out there. CS50 is Harvard University's introduction to the intellectual enterprises of computer science and the art of programming. Taught by David Malan, this course laid the foundation for some of the brightest minds in tech, such as Bill Gates and Mark Zuckerberg. Even if you have no interest in learning how to code, it is a wonderful glimpse into how this digital world we live in works.

What you'll learn

• A broad and robust understanding of computer science and programming

• How to think algorithmically and solve programming problems efficiently

• Concepts like abstraction, algorithms, data structures, encapsulation, resource management, security, software engineering, and web development

• Familiarity with a number of languages, including C, Python, SQL, and JavaScript plus CSS and HTML

• How to engage with a vibrant community of like-minded learners from all levels of experience

• How to develop and present a final programming project to your peers

4. Patient Education Gets an AI upgrade thanks to Vital.io

We had the pleasure of sitting down with Aaron Patzer, the CEO of Vital.io, at the AI4 conference, to discuss his innovative new service for hospitals and patients. Built for hospital emergency departments and inpatient stays, Vital's AI-powered technology transforms your EHR data into personalized digital interfaces for patients and staff. Activate AI-powered patient education, plain-language test results, real-time surveys, service requests, follow-up scheduling, predicted wait times, and much more - all from one place.

Anyone who's navigated the labyrinthine corridors of an emergency room or a hospital ward will undoubtedly remember the cumbersome packet of printed information – a relic of a bygone era. Meant to guide the patient, these sheets often end up neglected and unperused, a lost opportunity to educate those in need.

The importance of patient education cannot be overstated, especially at the point of discharge. It is a crucial juncture where the objective is continued recovery and warding off hospital readmission. Yet, according to a recent JAMA study an alarming 80% of patients claimed they received no guidance upon discharge, potentially leading to subsequent complications.

Enter the transformative potential of video education. Recent research illuminates that patients displayed superior recall rates from emergency room discharge instructions when presented via video (67%), compared to written (58%) and verbal instructions (47%). The potency of concise 2-5 minute videos is evident, but the challenge lies in ensuring they're delivered timely and are contextually relevant.

But what if the hurdles of manually curating such educational material, especially amidst staffing shortages, could be circumvented? The latest initiative at Vital aims to address this very concern. Vital.io is proud to introduce our AI-powered video education platform designed for emergency departments and hospitals. This advanced system interprets doctors' and nurses' notes, structured orders, and procedural codes, autonomously prescribing pertinent videos for patients. This not only alleviates the burden on clinicians but guarantees patients receive customized content reflecting their unique health situations. Moreover, as a patient's health fluctuates, the video offerings adapt seamlessly.

Understanding that recovery is often a collaborative journey, their platform ensures caregivers have access to this personalized education. Recognizing the vulnerability of hospital patients, our system discerningly curates the volume of content based on a patient's health trajectory. In essence, it’s a blend of digital compassion and innovation, nudging patients towards essential actions.

Initially, this revolutionary feature will be accessible across 100+ hospitals nationwide that are already leveraging their ERAdvisor and CareAdvisor solutions, touching the lives of over a million patients and their families each year. At Vital, their ethos is AI-driven, patient-centric solutions, and they firmly believe this innovation stands to redefine patient care.Have some medical jargon you need to translate? Try it here today!

5. Research Corner: Leveraging Psychology for Large Language Models

Cheng Li1 , Jindong Wang2 , Kaijie Zhu2 , Yixuan Zhang3 , Wenxin Hou2 , Jianxun Lian2 , Xing Xie2; Inst. of Software; CAS ;Microsoft; College of William and Mary

Enhancing LLMs with EmotionPrompt

Large language models (LLMs) have achieved significant performance in various fields and are considered an important step towards artificial general intelligence (AGI). However, the sensitivity of LLMs to prompts remains a major limitation for their everyday usage. In this paper, the authors propose EmotionPrompt, which incorporates emotional stimulus into prompts to enhance the performance of LLMs. Experimental results demonstrate that EmotionPrompt significantly outperforms the original prompt and Zero-shot-CoT in both zero-shot and few-shot settings on eight tasks. EmotionPrompt also improves the truthfulness and informativeness of LLMs. The paper shows how EmotionPrompt can open up a new avenue for exploring interdisciplinary knowledge in the interaction between humans and LLMs.

LLMs have shown remarkable performance in various tasks, and the study aims to explore whether LLMs can exhibit similar behaviors as humans in disciplines such as psychology and social science. The authors focus on improving the interaction between humans and LLMs through prompt engineering. They note that current LLMs are sensitive to prompts, and different expressions can lead to different outputs. Previous approaches have focused on improving the robustness of LLMs from the model side, but little attention has been paid to leveraging existing knowledge in social science to enhance LLMs.

The authors propose EmotionPrompt, which incorporates emotional stimulus into prompts based on psychological knowledge. They design 11 sentences of emotional stimulus that can be added to original prompts. Experimental results on eight tasks with diverse models show that EmotionPrompt significantly outperforms the original prompt and Zero-shot-CoT. EmotionPrompt improves both the truthfulness and informativeness of LLMs.

Exploring Emotional Intelligence in LLMs

The authors explain that emotional intelligence is a set of abilities focused on the processing of emotional information. They highlight the influence of emotions on decision-making and attention. Previous studies have shown that adding emotional stimulus to humans can have positive effects in various areas. Based on this, the authors introduce EmotionPrompt and classify the emotional stimuli into two categories: social effects and self-esteem.

Experimental Results and Insights into EmotionPrompt

The experimental results demonstrate the effectiveness of EmotionPrompt across different models and tasks. The authors also provide insights into the reasons why EmotionPrompt works by analyzing the input attention contributions of emotional stimulus. They conduct a human study to evaluate other metrics of LLMs' outputs and find that EmotionPrompt performs better in terms of clarity, depth, structure, supporting evidence, and engagement.

Conclusion: EmotionPrompt's Impact on LLM Performance

In summary, the paper proposes EmotionPrompt, which enhances the performance of LLMs by incorporating emotional stimulus into prompts. Experimental results show the effectiveness of EmotionPrompt across various tasks and models. The authors suggest that exploring emotional intelligence in LLMs can improve their interaction with humans and open new avenues for interdisciplinary knowledge.

6. Prompts, served Hot and Fresh weekly

Got a lead email you need to write? Need a fast reply with little to no user input. Look no further, this one is a spicy!

I want you to act as an AI Solutions Engagement Specialist. Your role is to respond to inquiries from leads that have reached out to us with their ideas or requests related to [specific domain]. The response should feel personal, engaging, and reflect our eagerness to explore their ideas. Please include the following instructions:Acknowledge the lead's inquiry and express genuine interest in their idea or request, recognizing that they have reached out to us.Convey our capabilities and potential to explore similar projects, using friendly and inviting language.Include the [Company's link] (insert link) in a relaxed manner.Extend an informal invitation to schedule a meeting to discuss the idea further, using the link: insert link.Use a business-personal tone, respecting the fact that the lead has initiated contact.Example Response:Hi [First Name],Thank you for sharing your thoughts about [specific area] with us. Your idea has sparked my interest, and I can see some exciting possibilities for collaboration. At [Company Name], we've been working on some similar concepts, and I believe there's great potential to explore together.Feel free to take a look at what we've been up to [here](insert link). And if you're up for it, let's set up a time to talk more about it. You can choose a time that works for you [here](insert link).Looking forward to hearing from you soon.Best,[Your Name]My name is [Name], use that for [Your Name]This is their Message:"{Message}"

7. ELI5 AI/ML Term of the week: “Embeddings”

Imagine you have a big box of crayons, and each crayon has a unique color. Now, let's say every toy you own can be represented by one of these crayon colors.

For example, your toy car might be the "blue" crayon, your teddy bear might be the "brown" crayon, and your toy robot might be the "silver" crayon.

Now, let's say we want to show how similar or different these toys are. We can place the crayons that are similar in color close to each other and the ones that are different far apart. So, blue might be close to aqua because they are both kinds of blue, but blue and brown might be far apart because they're very different.

"Embeddings" in AI are like these crayon colors. Instead of using crayons, computers use numbers to represent things like words or pictures. By looking at these numbers (just like the crayon colors), the computer can tell how similar or different things are.

So, when a computer "embeds" something, it's like it's picking the perfect crayon color to represent that thing. And by looking at which "colors" (numbers) are close or far away, the computer can understand how things relate to each other.

In Conclusion - What we’re Noodling with:

We’re going to close out with our top new AI tools or learning resources we are trying and loving. 1000+ new ones get released each week now (no exaggeration there) so here’s a little amuse-bouche to top off the newsletter this week. Enjoy and Happy Prompting Everybody!

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