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Reverse Image Search with Manticore Search

Parker Lennox
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Reverse Image Search with Manticore Search

Introduction

Reverse image search has changed how we discover digital content by allowing users to search using images instead of text. This technology has numerous applications, from helping shoppers find products to enabling designers to check their work against existing designs.

Understanding Reverse Image Search

How Does Reverse Image Search Work?

Reverse image search allows users to search by uploading an image or providing an image URL, and the system returns visually similar images along with related information. The process involves several key steps, utilizing vector search technology to efficiently handle high-dimensional image data:

  1. Feature Extraction: The system analyzes the image to identify key visual elements.
  2. Embedding Generation: Visual features are turned into a numerical vector representation.
  3. Similarity Comparison: This vector is compared against a database of stored image vectors using vector search.
  4. Result Ranking: Results are ordered by similarity scores.

The Role of Machine Learning Models

Machine learning models, particularly deep learning, have revolutionized reverse image search. Early systems in the 2000s relied on basic color histograms and edge detection, which limited accuracy. The introduction of Convolutional Neural Networks (CNNs) in 2012, like AlexNet, significantly improved the capability to understand complex visual patterns.

Building a Reverse Image Search System with TinyCLIP and Manticore Search

Vector Search and Manticore Search

Manticore Search, an open-source engine, supports vector search, making it a powerful choice for implementing reverse image search. We brought reverse image search to life with Manticore Search’s capabilities.

Implementing Reverse Image Search with Manticore Search

Practical Implementation

Here’s a practical implementation and basic workflow demonstrating what you can achieve with Manticore:

  • Upload image and get embeddings first
  • Implement image search using Manticore Search’s vector capabilities
  • Finally, do something with images found

Manticore Search Image Demo

We have developed a demo showcasing the capabilities of vector search, which you can explore at image.manticoresearch.com. This demo leverages TinyCLIP’s AI model to transform images into vectors and perform fast similarity searches.

Key Features

  • Reverse Image Search (Image-to-Image Search)
  • Text-to-Image Search (made possible by TinyCLIP’s ability to create text embeddings that match image embeddings)
  • Efficient CPU Processing

Applications of Reverse Image Search

E-commerce

  • Help customers find visually similar products by uploading a photo
  • Improve product discovery and enhance the shopping experience

Content Management

  • Identify duplicate images
  • Optimize storage space and ensure efficient content management
  • Track unauthorized usage of images across different platforms, maintaining copyright compliance

Recommendations

  • Provide visually relevant suggestions to users
  • Enhance user engagement by making it easy for users to discover related content

Conclusion and Future Directions

Reverse image search has come a long way, evolving from simple color matching to advanced vector-based similarity analysis. With models like TinyCLIP and Manticore Search, building a reverse image search system is now feasible for developers of all scales.

Frequently Asked Questions

Q: How does reverse image search work?

A: Reverse image search involves several key steps, including feature extraction, embedding generation, similarity comparison, and result ranking, utilizing vector search technology.

Q: What role do machine learning models play in reverse image search?

A: Machine learning models, particularly deep learning, have revolutionized reverse image search by improving the capability to understand complex visual patterns.

Q: What is Manticore Search?

A: Manticore Search is an open-source engine that supports vector search, making it a powerful choice for implementing reverse image search.

Q: How can I try out reverse image search?

A: You can try out our image search demo available at image.manticoresearch.com.

The Unspoken Truths of AI Development

Emerson Blake
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The Unspoken Truths of AI Development

DigitalOcean’s AI Plans: Democratizing AI for Startups and Small Businesses

As the cost of GPUs and LLMs continues to decline, DigitalOcean is poised to become a leading provider of infrastructure for AI development. The company’s VP of AI Advocacy and Partnerships, Dillon Erb, recently sat down with ZDNET to discuss DigitalOcean’s plans to make AI more accessible to startups and small businesses.

A Brief Overview of Dillon Erb’s Role

I was the co-founder and CEO of the first dedicated GPU cloud computing company called Paperspace. In July of 2023, Paperspace was acquired by DigitalOcean to bring AI tooling and GPU infrastructure to a whole new audience of hobbyists, developers, and businesses alike.

Exciting AI Projects at DigitalOcean

Expanding our GPU cloud to a much larger scale in support of rapid onboarding for a new generation of software developers creating the future of artificial intelligence.
Deep integration of AI tooling across the full DigitalOcean Platform to enable a streamlined AI-native cloud computing platform.
Bringing the full power of GPU compute and LLMs to our existing customer base to enable them to consistently deliver more value to their customers.

Challenges for Startups in the AI Space

Access to resources, talent, and capital are common challenges startups face when entering the AI arena.
Developing a good relationship with hardware suppliers or cloud providers like Paperspace can help startups, but the cost of purchasing or renting these machines quickly becomes the largest expense any smaller company will run into.

Barriers to Accessing Advanced AI Technologies

The cost of GPUs and LLMs is the most significant barrier to accessing advanced AI technologies for startups and small businesses.
Smaller companies may struggle to compete with larger companies due to the high cost of GPU computing and the difficulty in attracting and retaining AI talent.

Potential Consequences of Not Making AI Accessible

If startups and small businesses are unable to access advanced AI technologies, it could lead to stagnation and a lack of innovation in the field.
This could also lead to a lack of diverse research projects and potentially dangerous biases in AI development.

Misconceptions about AI Development for Startups

Startups may misinterpret the importance of infrastructure and software development in AI.
It’s common to meet people with fantastic ideas, but a misconception about how much work needs to be put into either of these areas.

How to Overcome the Knowledge Gap in AI Technology and Development

Hiring young entrepreneurs and enthusiasts making open-source technology popular is a great way to stay up on the knowledge you need to succeed.
Consider open-source options first, as many new businesses are repackaging existing, popular open-source resources.

Future Advancements in AI that will Benefit Startups and Growing Digital Businesses

The cost of LLMs (especially for inference) is declining rapidly, making AI more accessible to startups and small businesses.
Open-source model development is expanding rapidly, providing new tools and resources for AI development.

Final Thoughts for Startups Looking to Embark on their AI Journey

The emergence of LLMs like GPT has signaled a major leap in AI capabilities, and the entire development process has been upended.
AI is having an "API" moment, and it’s essential to understand the implications and opportunities this brings.

Conclusion

DigitalOcean’s plans to provide infrastructure for AI development and democratize AI for startups and small businesses have significant potential to shape the future of AI. By understanding the challenges and misconceptions surrounding AI development, entrepreneurs can overcome the knowledge gap and leverage the power of AI to drive innovation in their businesses.

Frequently Asked Questions

Q: What is the biggest barrier to accessing advanced AI technologies for startups?
A: The cost of GPUs and LLMs is the most significant barrier to accessing advanced AI technologies for startups and small businesses.

Q: How can startups overcome the knowledge gap in AI technology and development?
A: Hiring young entrepreneurs and enthusiasts making open-source technology popular is a great way to stay up on the knowledge you need to succeed. Consider open-source options first, as many new businesses are repackaging existing, popular open-source resources.

Q: What future advancements in AI do you foresee that will benefit startups and growing digital businesses?
A: The cost of LLMs (especially for inference) is declining rapidly, making AI more accessible to startups and small businesses. Open-source model development is expanding rapidly, providing new tools and resources for AI development.

Singapore’s AI-Driven Economic Revamp

Parker Lennox
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Singapore’s AI-Driven Economic Revamp

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The Future of AI Summit

The Financial Times’ Future of AI summit opened on November 6 with Josephine Teo, Singapore’s minister for digital development and information, talking to the FT’s analysis editor Geoff Dyer about Singapore’s AI strategy.

A Conversation on AI

The conversation between Teo and Dyer delved into how Singapore is navigating the technology’s promise and risks, and the implications of Donald Trump’s election to a second presidential term in the White House.

Key Takeaways

Some key takeaways from the conversation include:

* Singapore is prioritizing the development of AI in areas such as healthcare, finance, and education to improve efficiency and productivity.
* The government is also focusing on addressing the social and economic impacts of AI, such as job displacement and income inequality.
* Teo emphasized the importance of human judgment and oversight in AI decision-making to ensure that the technology is used in a responsible and ethical manner.

Watch the Conversation

You can watch the conversation between Josephine Teo and Geoff Dyer in the video below:

Stay Informed with Our Updates

To stay up-to-date on the latest developments in AI and the Future of AI summit, sign up for our Artificial intelligence myFT Digest.

FAQs

What is the Future of AI Summit?

The Future of AI summit is a series of events hosted by the Financial Times to explore the latest developments and implications of artificial intelligence.

Who was the guest speaker at the November 6 summit?

The guest speaker at the November 6 summit was Josephine Teo, Singapore’s minister for digital development and information.

What was discussed at the summit?

The summit focused on Singapore’s AI strategy, the implications of Donald Trump’s election to a second presidential term, and the responsible development and use of AI technology.

We Defied the Norm

Phil
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We Defied the Norm

Alex Daly: A Refreshing Twist on PR

Could you walk me through a typical day in your role?

I have built Daly so that I primarily focus on the high-level details that make the company what it is: its culture, new business, marketing, and vision. I find that approaching my role this way – versus overseeing client work – empowers my team to do their best work.

As a fully remote team, the day starts with everyone exchanging cute hellos with each other on Slack before diving into their respective tasks. Mine typically include catching up on proposals, connecting with my brilliant Managing Director & Partner Ally Bruschi about priorities for the day and week across culture and ops things (she keeps me focused, honest, and sane), and new business calls.

What was your early career like?

When I graduated from college I was on a professional trajectory to becoming a journalist. After working fact checking jobs at various magazines and picking up freelance writing gigs, I realized that journalism wasn’t my path. I had minored in film in college, and decided to give that industry a crack instead, so I took on a production role at a boutique documentary film company, which led me into the world of crowdfunding.

How did you get the title “The Crowdsourceress”?

In my role at the documentary firm, I was working as a production manager, managing a team, working on several film projects, and writing lots of grants to raise money for those projects. I found the grant writing process so slow and disheartening, but I wanted to stick with the job because I figured it could eventually lead me to higher positions in film. One day, a film editor told me about a documentary he was working on, and asked if I knew anything about Kickstarter (he had eyed my grant writing skills). This was 2012, and my short answer was: pretty much nothing.

While I didn’t know what crowdfunding was or how it worked, I told him I was game to help, and learned everything on the fly, from building the campaign page to Googling how to write a press release. We launched, and by the last day of the 30-day campaign, we had surpassed our goal by over 60 percent.

What was it like being named in Forbes’ 30 under 30?

Much like publishing my book, that time of my life was a bit foggy. I was managing too many crowdfunding campaigns without the right support system or company culture, and was feeling burnt out. It took me some time to submerge from that moment to have a deeper level of appreciation.

Still, I recall something very special at the time. When I made the Forbes list, I was already thinking about the next thing – new project, new challenge, new obstacle to overcome. I remember my mom telling me to pause and celebrate this win. We threw a party at my office, and I was surrounded by family, friends, colleagues, clients all celebrating this win, together. It was a lovely moment!

How inclusive is the design industry in 2024?

We’ve been lucky enough to work with some incredible designers and agencies at Daly. While a lot of progress has been made, there is still so much more to be done when it comes to inclusivity – and we find that the best work happens when these commitments come from within an organization.

A great example of a design company that has held themselves accountable and led the conversation on this front is the incredible team at SYLVAIN. Each year, they publish an Impact Assessment, including reports like Accountability Frameworks through which any consultancy can orient itself around progress, while also taking stock of their own performance to-date.

Do you think OCD has impacted your career?

Absolutely! I was diagnosed late in life, and both my perfectionist tendencies and obsessions got in the way of a lot, early on in my career. But what has impacted my career even more is the therapy I have been in for the past 5 years to treat my OCD. It has opened up my mind significantly, made me more self-aware, and empathic – both in my personal life, and as a professional and founder, too.

What are your favorite tools?

Monday.com, Google Drive, Slack.

What’s your dream project/dream client?

I have a few! Headspace, IDEO, Discord, Delta.

What do you think the PR industry needs to improve?

PR is an ever-changing landscape – with the most dramatic changes having unfolded since 2020. The most effective PR approach today is one that is both holistic and niche, and requires nimble, creative, media-obsessed comms folks who can think outside the box. Most agencies are really lacking in that department, and need to take a more proactive, modern approach to succeed.

What career advice would you give your younger self?

Keep going.

Alex Daly’s journey is a testament to the power of perseverance and creativity. From her early days as a journalist to her current role as a founder and CEO, she has consistently pushed boundaries and challenged herself to grow. Her commitment to inclusivity and her willingness to share her story openly are inspiring, and we are excited to see what the future holds for her and Daly.

Q: What inspired you to start Daly?
A: I was inspired by my own experiences as a crowdfunder and the need for a more holistic approach to PR.

Q: What sets Daly apart from other PR agencies?
A: Our focus on inclusivity and our willingness to think outside the box.

Q: What is your favorite part about being a founder and CEO?
A: The freedom to create and the opportunity to make a difference.

Q: What advice would you give to someone looking to start their own business?
A: Keep going!

HP Chromebook Plus 15: A Windows-Worthy Alternative?

Phil
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HP Chromebook Plus 15: A Windows-Worthy Alternative?

Here is the rewritten article:

HP Chromebook Plus 15a-nb0004na: Key Specifications

CPU: Intel Core i3 N305
Graphics: Intel UHD
Memory: 8GB LPDDR5 RAM
Screen size: 15.6in
Resolution: 1920×1080
Storage: 128GB UFS + microSD
Connectivity: Wi-Fi 6E, Bluetooth 5.3, 2x USB 3.2 Type-C (with DisplayPort and charging), 1x USB 3.2 Type-A, 1x 3.5mm audio
Dimensions: 36.26 x 24.15 x 1.98cm
Weight: 1.73kg

Design & Build

The HP Chromebook Plus wants you to think it’s a premium laptop, but it’s not. That’s not really a criticism, as you’re paying less than £500 for a 15.6-inch device so you’re not going to get one machined from aluminium and with military-grade protection ratings. However, the plastic shell is sturdy, the bezel isn’t particularly thick, there are USB-C ports and it’s the sort of colour that hints at a metal casing. Touch it, however, and you’ll instantly know that it’s something cheaper, but it does a good job of maintaining the illusion up until that point.

Features

If you’re an Android phone user, and tied into the Google ecosystem, then setting up a new Chromebook has become extremely easy. Scan a QR code from the laptop’s screen, authorise it on your phone, and the machine will be set up using the data stored in your Google account, so all your Chrome browser preferences and extensions will be there, you can open the Android App Store and install your apps, and it will even transfer your stored Wi-Fi passwords so you don’t need to bother entering them (though you’ll need to type one in at the very beginning of the setup process). Apart from downloading the latest updates for the OS, setup in this way is over very quickly and leaves you with a familiar environment that mirrors your PC browser.

Performance

Benchmark scores
Speedometer 10.5
JetStream 194.809
Mozilla Kraken 726.5ms
Geekbench 6 (Android)
Single core 1144
Multi-core 4230
GPU (Vulkan) 5429

Price

The HP Chromebook Plus 15 comes in at $599 in the US and £449 in the UK. At half the price of a MacBook Air, and still cheaper than many of the lowest-cost Windows laptops, a Chromebook can be an essential addition to your computer kit if you’re looking for something to do office work, presentations, the lightest of photo editing, and generally keep on top of emails and other collaborative jobs.

Who is it for?

HP’s Chromebook Plus is a portable office machine that will tick a lot of boxes if you’re already invested in Google’s cloud offerings and don’t want to spend a lot of money. Despite Google and Adobe’s attempts, this perhaps isn’t the best environment in which to attempt creative work, but for just about anything else it’s worth a look if you’re not looking to spend a lot of cash.

Buy it if…

  • You can do what you want to do on ChromeOS
  • You’re looking for a bargain PC
  • You’re already signed up to Google’s cloud

Don’t buy it if…

  • You need a Mac or Windows PC
  • You prefer to keep your documents stored offline
  • You want to play PC games (without streaming)

Also consider…

Conclusion:
The HP Chromebook Plus 15a-nb0004na is a budget-friendly laptop that offers a great balance of performance, features, and price. While it may not be suitable for demanding tasks like gaming or heavy video editing, it is an excellent choice for basic tasks like office work, browsing, and streaming. Its portability, durability, and ease of use make it an excellent option for those who want a reliable and affordable laptop.

FAQs:

Q: What is the price of the HP Chromebook Plus 15a-nb0004na?
A: The laptop is priced at $599 in the US and £449 in the UK.

Q: What is the processor speed of the HP Chromebook Plus 15a-nb0004na?
A:

Educators’ Comfort with AI

Morgan Tate
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Educators’ Comfort with AI

Key points:

  • A new survey reveals surprising information about who is more comfortable using AI in school.
  • While 34 percent of educators report using AI very frequently to draft or review assignments, only 24 percent of students do the same.
  • The 2024 AI in Academia Study by Copyleaks surveyed 1,000 students and 250 educators across the United States.

Frequent AI usage

  • Thirty-four percent of educators use AI very frequently to draft or review assignments, showing high adoption among educators.
  • Only 24 percent of students use AI this often, with 22 percent of students using it very rarely compared to just 12 percent of educators.

Enthusiasm for AI integration

  • Seventy percent of educators are keen on more AI integration in the classroom, indicating strong support for tech-enhanced teaching.
  • Meanwhile, 58 percent of students share this enthusiasm, reflecting a more modest interest in AI for their studies.

Optimism for personalized learning

  • A strong majority–87 percent of educators and 78 percent of students–believe AI can revolutionize education through personalized learning experiences.

Comfort and trust in AI tools

  • Thirty-one percent of educators express high comfort with AI-powered educational apps, slightly surpassing the 27 percent of students.
  • Trust in AI for study recommendations is nearly identical, with 28 percent of educators and 29 percent of students expressing strong confidence in these tools.

Significant unsanctioned AI usage

  • Educators and students differ greatly in following school AI ethics policies. Only 27 percent of educators claim to have misused AI tools, compared to 55 percent of students.
  • High school students have the highest rate of using AI tools in a sanctioned manner (63 percent), with males outpacing females 64 percent vs 51 percent.

Differing sentiments on understanding AI

  • A strong 68% of educators view understanding how AI works as very important, whereas only 41 percent of students share this perspective, highlighting a notable difference in sentiment toward AI literacy.

Awareness and recognition of AI detection

  • Both groups are highly aware of AI detection software, with 87% of students and educators acknowledging these tools for managing cheating and plagiarism.
  • Undergraduate educators had the highest rate of awareness (96 percent), while middle school educators had the lowest rate (75 percent).

Conclusion

The study highlights the need for clear guidelines and training to ensure AI enhances education responsibly. There is a gap between awareness and ethical use, especially among students, which needs to be addressed. The findings emphasize the need for targeted educational initiatives that empower educators and students to use AI effectively.

Frequently Asked Questions

Q: What is the primary purpose of the 2024 AI in Academia Study?
A: The study aims to explore the sentiments, trends, and practical applications of AI in education.

Q: How many educators and students participated in the study?
A: The study surveyed 1,000 students and 250 educators across the United States.

Q: What is the main finding of the study regarding AI usage among educators and students?
A: The study reveals that while 34 percent of educators use AI frequently, only 24 percent of students do the same.

Q: What is the significance of the study’s findings on AI integration in the classroom?
A: The study highlights the need for educators to be trained on AI ethics and responsible use, as well as the importance of empowering students to use AI effectively.

Planview’s Scalable AI Assistant for Portfolio and Project Management on Amazon Bedrock

Jordan Waverly
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Planview’s Scalable AI Assistant for Portfolio and Project Management on Amazon Bedrock

Solution Overview

Planview, a leading provider of connected work management solutions, embarked on an ambitious plan in 2023 to revolutionize how 3 million global users interact with their project management applications. To realize this vision, Planview developed an AI assistant called Planview Copilot, using a multi-agent system powered by Amazon Bedrock.

Technical Overview

Planview used key AWS services to build its multi-agent architecture. The central Copilot service, powered by Amazon Elastic Kubernetes Service (Amazon EKS), is responsible for coordinating activities among the various services. Its responsibilities include managing user session chat history using Amazon Relational Database Service (Amazon RDS), coordinating traffic between the router, application agents, and responder, and handling logging, monitoring, and collecting user-submitted feedback.

Router and Responder Sample Prompts

The router and responder components work together to process user queries and generate appropriate responses. The following prompts provide illustrative router and responder prompt templates. Additional prompt engineering would be required to improve reliability for a production implementation.

Model Evaluation and Selection

Evaluating and monitoring generative AI model performance is crucial in any AI system. Planview’s multi-agent architecture enables assessment at various component levels, providing comprehensive quality control despite the system’s complexity. Planview evaluates components at three levels: prompts, AI agents, and AI system.

Results and Impact

Over the past year, Planview Copilot’s performance has significantly improved through the implementation of a multi-agent architecture, development of a robust evaluation framework, and adoption of the latest FMs available through Amazon Bedrock. Planview saw the following results between the first generation of Planview Copilot developed mid-2023 and the latest version:

* Accuracy: Human-evaluated accuracy has improved from 50% answer acceptance to now exceeding 95%
* Response time: Average response times have been reduced from over 1 minute to 20 seconds
* Load testing: The AI assistant has successfully passed load tests, where 1,000 questions were submitted simultaneous with no noticeable impact on response time or quality
* Cost-efficiency: The cost per customer interaction has been slashed to one tenth of the initial expense
* Time-to-market: New agent development and deployment time has been reduced from months to weeks

Conclusion

In this post, we explored how Planview was able to develop a generative AI assistant to address complex work management process by adopting the following strategies:

* Modular development: Planview built a multi-agent architecture with a centralized orchestrator. The solution enables efficient task handling and system scalability, while allowing different product teams to rapidly develop and deploy new AI skills through specialized agents.
* Evaluation framework: Planview implemented a robust evaluation process at multiple levels, which was crucial for maintaining and improving performance.
* Amazon Bedrock integration: Planview used Amazon Bedrock to innovate faster with broad model choice and access to various FMs, allowing for flexible model selection based on specific task requirements.

About Authors

Sunil Ramachandra is a Senior Solutions Architect enabling hyper-growth Independent Software Vendors (ISVs) to innovate and accelerate on AWS. He partners with customers to build highly scalable and resilient cloud architectures. When not collaborating with customers, Sunil enjoys spending time with family, running, meditating, and watching movies on Prime Video.

Benedict Augustine is a thought leader in Generative AI and Machine Learning, serving as a Senior Specialist at AWS. He advises customer CxOs on AI strategy, to build long-term visions while delivering immediate ROI. As VP of Machine Learning, Benedict spent the last decade building seven AI-first SaaS products, now used by Fortune 100 companies, driving significant business impact. His work has earned him 5 patents.

Lee Rehwinkel is a Principal Data Scientist at Planview with 20 years of experience in incorporating AI & ML into Enterprise software. He holds advanced degrees from both Carnegie Mellon University and Columbia University. Lee spearheads Planview’s R&D efforts on AI capabilities within Planview Copilot. Outside of work, he enjoys rowing on Austin’s Lady Bird Lake.

FAQs

Q: What is Planview Copilot?
A: Planview Copilot is an AI assistant developed by Planview using a multi-agent system powered by Amazon Bedrock.

Q: What are the key components of Planview Copilot?
A: The key components of Planview Copilot include the router, responder, and application agents.

Q: How does Planview evaluate the performance of its AI models?
A: Planview evaluates its AI models at three levels: prompts, AI agents, and AI system.

Q: What are the benefits of using Amazon Bedrock for Planview Copilot?
A: Amazon Bedrock provides Planview with broad model choice and access to various FMs, allowing for flexible model selection based on specific task requirements.

Q: What are the results of Planview Copilot’s performance improvement?
A: Planview saw significant improvements in accuracy, response time, load testing, cost-efficiency, and time-to-market.

AI Granny Foils Phone Scammers

Emerson Blake
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AI Granny Foils Phone Scammers

Fighting Back Against AI Scams with an AI Grandma

Introducing Daisy, the AI Granny

At a time when AI scams are on the rise, one mobile operator is fighting back with an AI grandma. Virgin Media O2 has introduced "Daisy," an AI granny whose sole purpose is to answer the phone and keep scammers busy.

How Daisy Works

If a phone scammer happens to call one of the special numbers set up by the mobile company, an AI chatbot that’s "indistinguishable from a real person" answers the phone. O2 says it trained the elderly-woman-sounding chatbot on several cutting-edge AI technologies and several AI models. In addition, well-known YouTube scammers like Jim Browning helped with the training.

The AI’s Response

As the call progresses, the AI listens and transcribes the caller’s voice into text. A response is immediately generated through a custom large language model with a character personality layer and then run through a custom AI text-to-speech model that generates a reply. This happens in real-time, with no additional input needed.

Tying Up Scammers’ Time

Unfortunately for scammers, while she might sound vulnerable, Daisy isn’t an easy target. She might tell meandering stories about her grandkids or hobbies, be incredibly tech-illiterate, or give out wrong banking information that leads nowhere. Either way, she’s tying up scammer’s time and taking them away from real victims.

A Demo of Daisy’s Conversations

In a demo video, Daisy begins by not knowing what a website is and asks the person on the other end, "Three Ws then a dot?" She further explains that all she sees on her screen is a picture of her cat, Fluffy, and eventually trails off into a wandering story that prompts the exasperated caller to snap, "I think your profession is bothering people" and "It’s nearly been an hour!"

Conclusion

Daisy is so lifelike, as her creators explain, that she has successfully conversed with numerous fraudsters for 40 minutes at a time. In addition to the main goal being wasting time, Daisy has another purpose, which is to show people that you’re not always speaking to the person you think you are on the phone. O2 encourages customers to remain vigilant with any phone calls and report anything suspicious.

Frequently Asked Questions

Q: How does Daisy work?
A: Daisy is an AI chatbot that answers phone calls and responds to scammer’s queries in real-time.

Q: Is Daisy effective in stopping scams?
A: Yes, Daisy has successfully conversed with numerous fraudsters for 40 minutes at a time, tying up their time and taking them away from real victims.

Q: How was Daisy trained?
A: O2 trained Daisy on several cutting-edge AI technologies and several AI models, with the help of well-known YouTube scammers like Jim Browning.

Q: What is Daisy’s purpose?
A: Daisy’s main purpose is to waste scammers’ time and show people that you’re not always speaking to the person you think you are on the phone.

Interactive Articles

Parker Lennox
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Interactive Articles

Computing and Communication

Computing has changed how people communicate. The transmission of news, messages, and ideas is instant. Anyone’s voice can be heard. In fact, access to digital communication technologies such as the Internet is so fundamental to daily life that their disruption by government is condemned by the United Nations Human Rights Council.

A History of Computing and Communication

Parallel to the development of the internet, researchers like Alan Kay and Douglas Engelbart worked to build technology that would empower individuals and enhance cognition. Kay imagined the Dynabook in the hands of children across the world. Engelbart, while best remembered for his "mother of all demos," was more interested in the ability of computation to augment human intellect.

Recent Developments in Computing and Communication

More recent designs (though still historical by personal computing standards) point to a future where computers are connected and assist people in decision-making and communicating using rich graphics and interactive user interfaces.

Interactive Articles: Theory & Practice

Interactive articles draw from and connect many types of media, from static text and images to movies and animations. But in contrast to these existing forms, they also leverage interaction techniques such as details-on-demand, belief elicitation, play, and models and simulations to enhance communication.

Connecting People and Data

As visual designers are well aware, and as journalism researchers have confirmed empirically, an audience which finds content to be aesthetically pleasing is more likely to have a positive attitude towards it. This in turn means people will spend more time engaging with content and ultimately lead to improved learning outcomes.

Looking Forward

A diverse community has emerged to meet these challenges, exploring and experimenting with what interactive articles could be. The Explorable Explanations community is a "disorganized ‘movement’ of artists, coders & educators who want to reunite play and learning."

Conclusion

We believe in the power and untapped potential of interactive articles for sparking reader’s desire to learn and making complex ideas accessible and understandable to all.

FAQs

Q: What is an interactive article?
A: An interactive article is a digital publication that leverages interaction techniques such as details-on-demand, belief elicitation, play, and models and simulations to enhance communication.

Q: How do interactive articles facilitate communication and learning?
A: Interactive articles facilitate communication and learning by providing a dynamic and engaging way to present complex ideas and information, allowing readers to interact with the content and explore it in a more immersive way.

Q: What is the potential of interactive articles?
A: The potential of interactive articles is to make complex ideas accessible and understandable to all, to spark reader’s desire to learn, and to facilitate communication and learning in a more effective and engaging way.

Q: What is the current state of interactive articles?
A: The current state of interactive articles is that they are a growing trend in digital publishing, with a diverse community of authors, designers, and developers experimenting with what interactive articles could be and exploring their potential.

Q: What are the challenges of interactive articles?
A: The challenges of interactive articles include the need for improved tooling and platforms to support their creation, the need for more funding to support their development and publication, and the need for more research to identify the cases in which interactivity is worth the cost of creation.

Unlocking AI Video Recognition: How It Works and Why It Matters

Parker Lennox
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Unlocking AI Video Recognition: How It Works and Why It Matters

What is AI Video Recognition?

AI video recognition analyzes the content of a video stream to understand it, which encompasses detection, tracing, and identification of objects, scenes, and activities. This is one of the significant constituents of computer vision, which is all about interpreting visual data from the environment in an automated manner.

Video Object Recognition with TensorFlow API

TensorFlow is one of the most widely used open-source AI libraries and is the most efficient software for recognizing videos. It can quickly identify objects within a video using GPU acceleration technology.

Artificial Intelligence Technologies for Video Recognition

Many companies have become very skilled by using primarily open-source tools for visual information analysis. Consequently, today, we have a wide range of high-performance & platform-independent libraries and databases used in our day-to-day activities without coming down from cloud nine.

Major Challenges in AI Video Recognition

In the last few years, exceptional progress has been made, but certain difficulties remain in creating precise and robust video recognition systems. Some of the significant problems with video recognition include:

  • Scarcity of Labeled Data
  • Real-Time Performance
  • Smart City Management

How to Label Videos in V7?

  • Step 1: Define Your Model’s Inputs and Outputs
  • Step 2: Upload Your Data to V7
  • Step 3: Label Your Video Dataset
  • Step 4: Review Your Annotations
  • Step 5: Train Your Video Recognition Model
  • Step 6: Evaluate Your Model’s Performance

Best APIs for Seamless Video Recognition Integration

  • Google Video Intelligence API: has a broad selection of features that can be used to detect objects within videos.
  • Amazon Rekognition: offers many pre-trained models as well as tools that are used to train models independently.
  • Microsoft Image Processing API: Contains numerous user-friendly algorithms for detecting objects in videos.

Wrapping Up

Video recognition has become an important technology that has changed many professions by automatically analyzing large amounts of video data. It can be used for security purposes, shopping without cashiers, and traffic flow management, among others. As advancements are made in these areas, it will be possible to improve upon them so that business operations become much more efficient and safe through automation.

FAQs

Q: What is AI video recognition?
A: AI video recognition analyzes the content of a video stream to understand it, which encompasses detection, tracing, and identification of objects, scenes, and activities.

Q: What are some of the major challenges in AI video recognition?
A: Some of the significant problems with video recognition include scarcity of labeled data, real-time performance, and smart city management.

Q: How can I label videos in V7?
A: You can define your model’s inputs and outputs, upload your data to V7, label your video dataset, review your annotations, train your video recognition model, and evaluate your model’s performance.

Q: What are some of the best APIs for seamless video recognition integration?
A: Some of the best APIs for seamless video recognition integration include Google Video Intelligence API, Amazon Rekognition, and Microsoft Image Processing API.

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