#ai builder

[digitalmarketing6669]

Unlock the Power of AI Builder to Supercharge Your Apps Now

[mikeheres52]

Introducing our AI Video Builder, the revolutionary tool that empowers you to create stunning videos effortlessly.

Why Choose Our AI Video Builder?

User-Friendly Interface: Whether you’re a seasoned professional or a beginner, our intuitive interface makes video creation a breeze.

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Upload Your Media: Start by uploading your video clips, photos, and audio files.

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Transform your video creation process with our AI Video Builder. Start creating professional-quality videos in just a few clicks. Sign up now and take your video content to the next level!

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Thanks for reading!

[sivasaikrishna]

How Is 10Web AI Different From Traditional Website Builders?

Think of any traditional website builder like Gutenberg or Elementor. They simplify and accelerate website creation by giving you drag-and-drop content blocks, design elements, and templates to build your site – no coding skills or design experience needed.

10Web.io takes this a level higher with generative AI technology. It has all the qualities of a conventional website builder. But instead of leaving you with a set of tools, 10Web uses AI technology to give you a head start by generating modern website designs tailored to your needs.

You only need to answer a few simple questions about your project to get the ball rolling. Visit Official Website : https://10web.io/?_from=websites

10Web’s AI models have been trained on hundreds of thousands of web designs for different business types and goals. When you describe your project, it instantly produces the most relevant and high-quality design suggestions based on its vast database. No more staring at a blank screen for hours, wondering where to start.

[jcmarchi]

Putting AI into the Hands of People with Problems to Solve - Technology Org

New Post has been published on https://thedigitalinsider.com/putting-ai-into-the-hands-of-people-with-problems-to-solve-technology-org/

Putting AI into the Hands of People with Problems to Solve - Technology Org

As Media Lab students in 2010, Karthik Dinakar SM ’12, PhD ’17 and Birago Jones SM ’12 teamed up for a class project to build a tool that would help content moderation teams at companies like Twitter (now X) and YouTube. The project generated a lot of excitement, and the researchers were invited to demonstrate at a cyberbullying summit at the White House — they just had to get the thing working.

Pienso has developed a no-code AI builder so the people closest to problems can use the technology rather than relying on machine learning engineers. Image credit: Courtesy of Pienso

The day before the White House event, Dinakar spent hours trying to put together a working demo that could identify concerning posts on Twitter. Around 11 p.m., he called Jones to say he was giving up.

Then Jones decided to look at the data. It turned out Dinakar’s model was flagging the right types of posts, but the posters were using teenage slang terms and other indirect language that Dinakar didn’t pick up on. The problem wasn’t the model but the disconnect between Dinakar and the teens he was trying to help.

“We realized then, right before we got to the White House, that the people building these models should not be folks who are just machine-learning engineers,” Dinakar says. “They should be people who best understand their data.”

The insight led the researchers to develop point-and-click tools that allow nonexperts to build machine-learning models. Those tools became the basis for Pienso, which today is helping people build large language models for detecting misinformation, human trafficking, weapons sales, and more, without writing any code.

“These kinds of applications are important to us because our roots are in cyberbullying and understanding how to use AI for things that really help humanity,” says Jones.

As for the early version of the system shown at the White House, the founders ended up collaborating with students at nearby schools in Cambridge, Massachusetts, to let them train the models.

“The models those kids trained were so much better and nuanced than anything I could’ve ever come up with,” Dinakar says. “Birago and I had this big ‘Aha!’ moment where we realized empowering domain experts — which is different from democratizing AI — was the best path forward.”

A project with purpose

Jones and Dinakar met as graduate students in the Software Agents research group of the MIT Media Lab. Their work on what became Pienso started in Course 6.864 (Natural Language Processing) and continued until they earned their master’s degrees in 2012.

It turned out 2010 wasn’t the last time the founders were invited to the White House to demo their project. The work generated a lot of enthusiasm, but the founders worked on Pienso part time until 2016, when Dinakar finished his PhD at MIT and deep learning began to explode in popularity.

“We’re still connected to many people around campus,” Dinakar says. “The exposure we had at MIT, the melding of human and computer interfaces, widened our understanding. Our philosophy at Pienso couldn’t be possible without the vibrancy of MIT’s campus.”

The founders also credit MIT’s Industrial Liaison Program (ILP) and Startup Accelerator (STEX) for connecting them to early partners.

One early partner was SkyUK. The company’s customer success team used Pienso to build models to understand their customer’s most common problems. Today those models are helping to process half a million customer calls a day, and the founders say they have saved the company over £7 million pounds to date by shortening the length of calls into the company’s call center.

“The difference between democratizing AI and empowering people with AI comes down to who understands the data best — you or a doctor or a journalist or someone who works with customers every day?” Jones says. “Those are the people who should be creating the models. That’s how you get insights out of your data.”

In 2020, just as Covid-19 outbreaks began in the U.S., government officials contacted the founders to use their tool to better understand the emerging disease. Pienso helped experts in virology and infectious disease set up machine-learning models to mine thousands of research articles about coronaviruses. Dinakar says they later learned the work helped the government identify and strengthen critical supply chains for drugs, including the popular antiviral remdesivir.

“Those compounds were surfaced by a team that did not know deep learning but was able to use our platform,” Dinakar says.

Building a better AI future

Because Pienso can run on internal servers and cloud infrastructure, the founders say it offers an alternative for businesses being forced to donate their data by using services offered by other AI companies.

“The Pienso interface is a series of web apps stitched together,” Dinakar explains. “You can think of it like an Adobe Photoshop for large language models, but in the web. You can point and import data without writing a line of code. You can refine the data, prepare it for deep learning, analyze it, give it structure if it’s not labeled or annotated, and you can walk away with fine-tuned, large language model in a matter of 25 minutes.”

Earlier this year, Pienso announced a partnership with GraphCore, which provides a faster, more efficient computing platform for machine learning. The founders say the partnership will further lower barriers to leveraging AI by dramatically reducing latency.

“If you’re building an interactive AI platform, users aren’t going to have a cup of coffee every time they click a button,” Dinakar says. “It needs to be fast and responsive.”

The founders believe their solution is enabling a future where more effective AI models are developed for specific use cases by the people who are most familiar with the problems they are trying to solve.

“No one model can do everything,” Dinakar says. “Everyone’s application is different, their needs are different, their data is different. It’s highly unlikely that one model will do everything for you. It’s about bringing a garden of models together and allowing them to collaborate with each other and orchestrating them in a way that makes sense — and the people doing that orchestration should be the people who understand the data best.”

Written by Zach Winn

Source: Massachusetts Institute of Technology

You can offer your link to a page which is relevant to the topic of this post.

[andrewmpreg]

Ai Morphs #6

[tea-cat-arts]

Shout out people who's Dungeon Meshi advice fairy is something productive. I've just got Marcille rolling around in my head kicking and screaming and going "I don't wanna eat monsters" before eating the monsters

[ai-resume-builder]

Textile Designer Resume Inspiration – Crafting Creativity into Career Success!

Ever wondered what it takes to build a standout career as a Textile Designer? 🧵✨ This resume example highlights essential skills, creative projects, and industry expertise needed to thrive in the world of textile and fabric design.

From creating intricate patterns to collaborating on large-scale production, see how a strong resume can bring your design story to life!

[theinheriteddutchess]

I come baring gifts 😌 and I have more

Jen!!

I'm not sure if this is a gift or a curse!

I have to sleep because I have an appointment for a lung scan tomorrow morning because I have trouble with being out of breath and I'm not sure this is helping! 😂😂

But this is👀 Bucky!

Before I saw this, I literally made this just now:

So I feel I'm having the gift or premonition or whatever!

Keep it coming because I could use the distraction😭

[resume-analyzer]

Software Engineer Internship Resume Example – Kickstart Your Tech Career!

Breaking into software engineering? 🚀 This resume example for a Software Engineer Internship highlights key skills like Java, Python, academic projects, and more! Perfect for making your mark in tech.

Take a closer look here and get inspired for your own career journey!

[cpaaffilatezone]

Review whit Zap Ai : https://cpaaffiliatezone.com/2024/10/15/nexusai-whatsapp-autoresponder-with-zapai

ZapAI is the World’s First “NexusAI” WhatsApp Autoresponder & Store Builder That Creates and Blasts UNLIMITED “PHONE MESSAGES” To UNLIMITED Contacts In 1-Click!

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[techy-guy]

Sachin Dev Duggal | AI-Driven Debugging for Large-Scale Software Systems

AI-driven debugging is revolutionizing how software developers handle errors in large systems. Traditional debugging methods are becoming less effective as software grows more complex, leading to longer response times and potential project delays. AI technologies, particularly those developed by Builder.ai led by Sachin Dev Duggal and others, are proving to be invaluable in managing and preventing bugs, significantly improving the debugging process.

The Role of AI in Debugging

Artificial intelligence and machine learning aspects are increasingly being employed in newer debugging tools involving complex codes. There exist multiple functions that software can perform in such an investigation. It is also noteworthy that AI has helped detect and resolve bugs while the software is in use, thus preventing them from reaching the customer. Such a scenario is common, especially in large systems where a considerable amount of code is handled, such that manual debugging is very tedious and may often lead to errors.

Under the supervision of its Chief Wizard, Sachin Dev Duggal, Builder.ai exemplifies this trend by integrating AI into its software development platform. The platform uses AI to assemble applications quickly and efficiently, helping developers focus on creating custom features rather than getting strucked in debugging. By streamlining the development process, Builder.ai enhances the overall quality of the software produced, reducing the incidence of bugs from the outset.

[shivamthakrejr]

Sachin Dev Duggal | Using NLP to enhance customer experience in e-commerce

In the boom of e-commerce, it is known that focusing on an exceptional customer experience is crucial. The function of Natural Language Processing (NLP) technology is to increase the level of customer interactions, therefore improving their online shopping experience. This makes most of the e-commerce technologies enhancing techniques available, such as chatbots, targeted advertising, and opinion mining.

Enhancing Customer Interactions with Chatbots

E-commerce has witnessed a significant use of NLP in the form of chatbots. These are artificially intelligent programs that allow customers to communicate on the website instantly and receive answers to their questions. Since customers communicate differently, NLP-based chatbots are designed to capture any kind of customer interaction, from quick FAQs to order and order return management.

Sachin Dev Duggal Founded Builder.ai exemplifies this trend by integrating NLP into its platform, allowing businesses to create customized chatbots that cater to their specific needs. Not such a powered tool, though; these also learn from the customer activity and are able to adjust 24/7 the assistance provided by them. Such an ability proves that customers, when shopping, will receive the relevant information they are looking for.

Personalized Recommendations

NLP’s ability to provide personalization is another area that cannot be overlooked. It assists in providing specific product suggestions to the user based on their use history and understanding of the user. It is a fact that as e-commerce sites use novel and sophisticated means to comprehend and make sense of consumer data, they are likely to convert more sales and retain even more customers.

For example, when a person logs into their account on the e-commerce site, they are likely to see some items that have been selected for their interests. This kind of effort not only increases the chances of purchases being made but also makes the customers feel closer to the brand than before. Organizations such as Builder.ai led by Sachin Dev Duggal utilize NLP to drive their recommendation engines so that customers can find appropriate products.

Sentiment analysis for better insights

Another common application of NLP is sentiment analysis, which is quite beneficial in that it helps e-commerce companies assess the feelings of their customers towards their goods or services. Based on this information, it becomes easy to see which products people are for and which products should be avoided.

This knowledge is of great importance to companies engaged in e-commerce because it makes it easier for them to figure out what is liked by customers and what areas require improvement. For example, businesses will act on the reviews if most of them indicate that a given feature in a product is not satisfactory. Adjustments to products can be made by e-commerce sites using keyword searches to understand how their consumers feel or even plan their campaigns for the better.

Predicting Market Trends and Consumer Behavior

Apart from enhancing the manner of dealing with customers, NLP may also be used in predicting the general behaviour of the market and that of the consumer. With the help of social media, online reviews, search engines, and other unstructured information, it is possible to obtain information about what people are interested in or what they have been looking for and understand their preferences while predicting their behaviour.

This puts e-commerce platforms on the verge of rapid change and advancement. Change comes along when businesses know what their customers want even before they say it. Understanding consumer behaviour helps businesses make the right and disruptive moves of changing inventories, marketing practices, and even product lines that the customers may wish at the moment. Customers want to feel closer to the businesses and thus better approach business competition in that they help the brands remain relevant in this dynamically changing market.

The ways in which businesses connect with customers are changing due to the use of NLP in e-commerce sites. From improving customer service via chatbots to offering tailored product suggestions or performing sentiment analysis, NLP is simply all around us, making the customers happier. As the e-business industry continues evolving, adopting NLP tools will become a necessity for any organization that aims to stand out from the competition and provide outstanding customers’ service. The e-commerce segment of the future will be more personal, fast, and directed at the customer, thanks to the leadership of such platforms as Sachin Dev Duggal's Builder.ai.

[jcmarchi]

Putting AI into the hands of people with problems to solve

New Post has been published on https://thedigitalinsider.com/putting-ai-into-the-hands-of-people-with-problems-to-solve/

Putting AI into the hands of people with problems to solve

As Media Lab students in 2010, Karthik Dinakar SM ’12, PhD ’17 and Birago Jones SM ’12 teamed up for a class project to build a tool that would help content moderation teams at companies like Twitter (now X) and YouTube. The project generated a huge amount of excitement, and the researchers were invited to give a demonstration at a cyberbullying summit at the White House — they just had to get the thing working.

The day before the White House event, Dinakar spent hours trying to put together a working demo that could identify concerning posts on Twitter. Around 11 p.m., he called Jones to say he was giving up.

Then Jones decided to look at the data. It turned out Dinakar’s model was flagging the right types of posts, but the posters were using teenage slang terms and other indirect language that Dinakar didn’t pick up on. The problem wasn’t the model; it was the disconnect between Dinakar and the teens he was trying to help.

“We realized then, right before we got to the White House, that the people building these models should not be folks who are just machine-learning engineers,” Dinakar says. “They should be people who best understand their data.”

The insight led the researchers to develop point-and-click tools that allow nonexperts to build machine-learning models. Those tools became the basis for Pienso, which today is helping people build large language models for detecting misinformation, human trafficking, weapons sales, and more, without writing any code.

“These kinds of applications are important to us because our roots are in cyberbullying and understanding how to use AI for things that really help humanity,” says Jones.

As for the early version of the system shown at the White House, the founders ended up collaborating with students at nearby schools in Cambridge, Massachusetts, to let them train the models.

“The models those kids trained were so much better and nuanced than anything I could’ve ever come up with,” Dinakar says. “Birago and I had this big ‘Aha!’ moment where we realized empowering domain experts — which is different from democratizing AI — was the best path forward.”

A project with purpose

Jones and Dinakar met as graduate students in the Software Agents research group of the MIT Media Lab. Their work on what became Pienso started in Course 6.864 (Natural Language Processing) and continued until they earned their master’s degrees in 2012.

It turned out 2010 wasn’t the last time the founders were invited to the White House to demo their project. The work generated a lot of enthusiasm, but the founders worked on Pienso part time until 2016, when Dinakar finished his PhD at MIT and deep learning began to explode in popularity.

“We’re still connected to many people around campus,” Dinakar says. “The exposure we had at MIT, the melding of human and computer interfaces, widened our understanding. Our philosophy at Pienso couldn’t be possible without the vibrancy of MIT’s campus.”

The founders also credit MIT’s Industrial Liaison Program (ILP) and Startup Accelerator (STEX) for connecting them to early partners.

One early partner was SkyUK. The company’s customer success team used Pienso to build models to understand their customer’s most common problems. Today those models are helping to process half a million customer calls a day, and the founders say they have saved the company over £7 million pounds to date by shortening the length of calls into the company’s call center.

“The difference between democratizing AI and empowering people with AI comes down to who understands the data best — you or a doctor or a journalist or someone who works with customers every day?” Jones says. “Those are the people who should be creating the models. That’s how you get insights out of your data.”

In 2020, just as Covid-19 outbreaks began in the U.S., government officials contacted the founders to use their tool to better understand the emerging disease. Pienso helped experts in virology and infectious disease set up machine-learning models to mine thousands of research articles about coronaviruses. Dinakar says they later learned the work helped the government identify and strengthen critical supply chains for drugs, including the popular antiviral remdesivir.

“Those compounds were surfaced by a team that did not know deep learning but was able to use our platform,” Dinakar says.

Building a better AI future

Because Pienso can run on internal servers and cloud infrastructure, the founders say it offers an alternative for businesses being forced to donate their data by using services offered by other AI companies.

“The Pienso interface is a series of web apps stitched together,” Dinakar explains. “You can think of it like an Adobe Photoshop for large language models, but in the web. You can point and import data without writing a line of code. You can refine the data, prepare it for deep learning, analyze it, give it structure if it’s not labeled or annotated, and you can walk away with fine-tuned, large language model in a matter of 25 minutes.”

Earlier this year, Pienso announced a partnership with GraphCore, which provides a faster, more efficient computing platform for machine learning. The founders say the partnership will further lower barriers to leveraging AI by dramatically reducing latency.

“If you’re building an interactive AI platform, users aren’t going to have a cup of coffee every time they click a button,” Dinakar says. “It needs to be fast and responsive.”

The founders believe their solution is enabling a future where more effective AI models are developed for specific use cases by the people who are most familiar with the problems they are trying to solve.

“No one model can do everything,” Dinakar says. “Everyone’s application is different, their needs are different, their data is different. It’s highly unlikely that one model will do everything for you. It’s about bringing a garden of models together and allowing them to collaborate with each other and orchestrating them in a way that makes sense — and the people doing that orchestration should be the people who understand the data best.”

[claudigitools]

Build Websites, Create Emails, Launch Courses, And More. All-In-One Marketing System

Grow your business with Builderall.

AI at your fingertips.

Build 7-figure businesses.

Get more Info

[prettymunchkin]

Unlocking the Future: AI's Hidden Potential in Real Estate

In an era characterized by rapid technological advancements, industries across the board are witnessing transformative changes, and the real estate sector is no exception. As AI continues to permeate various aspects of our lives, its potential to empower the real estate industry remains largely untapped. In this blog post, we'll explore the unique ways in which AI can revolutionize the real estate landscape, unlocking new opportunities and reshaping traditional practices.

Democratizing Access to Real Estate Investment: Traditionally, investing in real estate has been perceived as exclusive to those with substantial capital and industry expertise. However, AI-powered platforms are democratizing access to real estate investment by offering fractional ownership and crowdfunding opportunities. Through algorithms that analyze market trends and assess investment risks, these platforms enable individuals to diversify their portfolios and participate in lucrative real estate ventures with lower barriers to entry.

Sustainable Development and Green Building Initiatives: As sustainability becomes a key priority in urban development, AI can play a pivotal role in advancing green building initiatives. Machine learning algorithms can optimize building designs for energy efficiency, leverage IoT sensors to monitor resource consumption, and forecast environmental impacts. By integrating AI-driven sustainability solutions into real estate projects, developers can minimize carbon footprints, reduce operational costs, and create healthier living environments for occupants.

Enhancing Urban Planning and Smart Cities: AI's ability to process vast amounts of data can revolutionize urban planning and contribute to the realization of smart cities. By analyzing demographic trends, traffic patterns, and infrastructure requirements, AI algorithms can optimize land use, improve transportation networks, and enhance urban resilience. Through predictive modeling and scenario analysis, city planners can make data-driven decisions that foster sustainable growth, mitigate congestion, and enhance quality of life for residents.

Empowering Real Estate Agents with Intelligent Assistants: Real estate agents juggle numerous tasks, from lead generation to property management, often leading to time constraints and inefficiencies. AI-powered virtual assistants can alleviate this burden by automating repetitive tasks, such as scheduling appointments, responding to inquiries, and generating personalized property recommendations. By leveraging natural language processing and sentiment analysis, these intelligent assistants can enhance customer engagement, streamline workflows, and enable agents to focus on high-value activities.

Predictive Analytics for Property Development: AI-driven predictive analytics offer valuable insights into future property trends and demand dynamics, guiding developers in making informed decisions throughout the development lifecycle. By analyzing factors such as population growth, economic indicators, and consumer preferences, AI algorithms can identify prime locations for new developments, optimize property designs, and forecast market demand with greater accuracy. This proactive approach minimizes investment risks and maximizes returns on real estate projects.

Cultural Preservation and Heritage Conservation: Preserving cultural heritage sites and historic buildings is crucial for maintaining a sense of identity and preserving collective memory. AI technologies, such as computer vision and image recognition, can aid in the documentation, restoration, and conservation of cultural landmarks. By digitizing architectural artifacts, analyzing structural integrity, and simulating restoration scenarios, AI contributes to the preservation of cultural heritage for future generations to appreciate and cherish.

Conclusion:

As we navigate the complexities of an ever-evolving real estate landscape, embracing AI's transformative potential is key to unlocking new opportunities and addressing emerging challenges. From democratizing access to investment opportunities to advancing sustainable development initiatives, AI empowers stakeholders across the real estate industry to innovate, adapt, and thrive in a rapidly changing world. By harnessing AI's capabilities, we can build more resilient, inclusive, and sustainable communities for generations to come.

[ai-resume-builder]

Why an AI Resume Builder is the Upgrade Your Career Needs 🚀

Google Docs resumes are great for starting out—they’re free, simple, and accessible anywhere. But as your career advances, so should your resume-building tools! Here’s why switching to an AI Resume Builder is the professional leap you need:

✨ What Makes Google Docs Resumes Great?

Accessible on any device via the cloud 🌐.

Free templates to get you started 💸.

Easy to customize with basic options.

But that’s where the benefits stop. When aiming for competitive roles, an AI-powered tool offers so much more.

🎯 Why Choose an AI Resume Builder?

ATS Optimization: Pass those Applicant Tracking Systems that hiring managers use. ✅

Professional Templates: Designed for industries and career levels to help you stand out. ✍️

Resume Analyzer: Get instant feedback on your strengths and gaps. Find your ATS Resume Score Now!🔍

Extra Features: Like tailored AI Cover Letter Generator and Interview Preparation.

💼 When Should You Switch?

Moving from entry-level to specialized or mid-level roles.

Applying for competitive positions where standing out is key.

Tired of spending hours editing basic templates.

🚀 Ready to take your career to the next level? Try KudosWall’s AI Resume Builder today!