Tag Archives: ai

Top Websites to Transform Your 2023


In today’s digital age, the internet has become an integral part of our daily lives. With so many websites to choose from, it can be overwhelming to know which ones are the most useful and worth your time. In this article, we will introduce you to a selection of the Top Websites to Transform Your 2023 that we believe everyone should know about. These websites offer valuable resources, tools, and services that can make your life easier, more productive, and more enjoyable. Are you ready to make this your best year ever? From search engines and social media platforms to online shopping and entertainment. These websites are essential to navigating the online world and making the most of your online experience.


Hunter is a website that provides tools for finding and verifying email addresses. It allows you to search for email addresses associated with a particular domain, or to find the email addresses of people working at a particular company. You can use Hunter to build email lists, verify the accuracy of your existing lists, and integrate its services with other software.

Hunter offers several paid plans with different features and limits on the number of searches you can perform per month. It also has a free plan that allows you to perform a limited number of searches per day.

In addition to its email search and verification tools, Hunter also provides a range of other resources for professionals and businesses, including a blog with tips on email marketing and outreach, and integrations with popular CRM and marketing automation platforms.


Playground AI is a web app that allows users to create and share AI art with a community. It offers a range of features that set it apart from other text-to-image generation websites. Firstly, it offers free Dall-E2 image generation, which is a rare feature among competitors. It also automatically fills in text prompts according to the desired art style, saving users time and effort in crafting the perfect prompt. In addition, it allows users to upscale their images for free and saves all generated images on the server so that users can access them in full resolution at any time. Finally, Playground AI is also a social media platform for AI art, allowing users to share, appreciate, and discover creations by other artists. Although Playground AI is currently free to use, it may eventually charge a fee in the future.


Revolancer is a website that connects businesses with freelancers who can help them with various tasks and projects. It allows businesses to find and hire freelancers in a range of categories, including web development, graphic design, marketing, and more.

Freelancers can use Revolancer to find and apply for freelance opportunities and to manage their work and payments. The website offers a range of tools and resources for both businesses and freelancers, including a marketplace for finding and hiring talent, a project management platform, and a payment system.

Revolancer aims to make it easier for businesses to find and hire skilled freelancers, and for freelancers to find and complete projects. It is designed to be a one-stop platform for businesses and freelancers to connect, communicate, and collaborate on projects.


Wolfram Alpha is a computational knowledge engine developed by Wolfram Research. It is not a search engine in the traditional sense, as it does not search the web for information. Instead, it uses a vast collection of algorithms and data to generate answers and provide information on a wide range of topics.

Wolfram Alpha can be used to perform calculations, solve equations, and look up facts and figures on a wide range of subjects, including math, science, finance, history, and more. It can also create graphs and plots, generate reports and documents, and provide interactive simulations and visualizations.

In addition to its web-based interface, Wolfram Alpha is also available as a mobile app and as an API that can be integrated into other websites and applications.


Debuild is a start-up that is building a machine learning-powered development tool that takes in plain English and outputs runnable code for web applications. They are using the advanced natural language processing capabilities of OpenAI’s GPT-3 model to translate English into code quickly and accurately. The demand for no-code solutions has increased significantly in recent years, and Debuild aims to provide a solution for aspiring builders who have ideas but lack programming skills. The company was founded in 2020 and is based at the University of Maryland. They have raised funding from investors and have gained significant traction on social media, with over 30,000 likes and retweets on Twitter. The team behind Debuild includes a serial entrepreneur and an experienced engineer. The company’s mission is to give everyone the ability to create valuable software.

Wrapping Up

In conclusion, the websites mentioned in this article are a valuable resource for anyone looking to improve their online experience in 2023. From searching for information to connecting with others on social media, these websites offer a range of tools and services that can enhance efficiency, productivity, and enjoyment. Whether you are a professional, business owner, or individual, these websites are worth considering as you navigate the digital landscape. By familiarizing yourself with these websites and utilizing their resources, you can make the most of your online experience and stay up-to-date with the latest developments in the digital world.

If you enjoyed this article, be sure to check out our other pieces for more information and insights.

Machine Vision with Raspberry Pi using TensorFlow and OpenCV4

artificial vision with raspberry pi tensorflow and opencv

Do you want to implement a CCTV camera that can identify several different elements? Or maybe optimize your robot and give it the ability to detect objects?

The Raspberry Pi 4 offers enough performance to perform machine learning. In this tutorial you will see the steps to get TensorFlow working on your Raspberry Pi 4, as well as a demonstration of detecting objects with a PI Camera or USB Webcam.

Required Hardware/software

  • Raspberry Pi 4.
  • 3000mA power supply with its USB-C cable.
  • micro-SD card (minimum 32 GB).
  • Picamera (or USB webcam).

What is TensorFlow ?

TensorFlow is an open source machine learning framework for solving complex mathematical problems. It allows researchers to develop experimental learning architectures and turn them into software. TensorFlow was developed by Google Brain team in 2011 and made open source in 2015. Since then it has gone through more than 21000 changes and upgraded to version 1.0 in February 2017. Currently version 2.8.0 is available on the TensorFlow website.

This library notably makes it possible to train and run neural networks for the classification of handwritten digits, image recognition, models for machine translation, and natural language processing. An application’s code is written in Python but executed in high-performance C++. Here, the raspberry and its camera will be able to detect a hundred different objects! In addition, good results are obtained at night with an IR camera equipped with LEDs.

On the software side, the micro-SD has been flashed with the latest version of Raspbian Buster downloadable from the official website. Python3 is installed there by default, to launch a program from the command line, you will have to type in a terminal:

$ python3 my_program.py

Here, the Object_detection_picamera.py program will need several elements to work:

  • The mscoco_label_map.pbtext file corresponding to the list of 100 detectable objects, it is located in the data folder.
  • The “ssdlite_mobilenet_v2_coco_2018_05_09” folder where the training model files are stored.
  • The utils folder (utilities) containing the classification modules for the various objects.

Installing TensorFlow

Start by updating the Raspberry Pi:

sudo apt-get update
sudo apt-get dist-upgrade

Next, install TensorFlow with the pip3 command.

sudo pip3 install tensorflow

TensorFlow needs a library named Atlas, type the following command:

sudo apt-get install libatlas-base-dev

Finally, it will be necessary to install the dependencies necessary for the detection of objects.

sudo pip3 install pillow lxml jupyter matplotlib cython
sudo apt-get install python-tk

That’s it for TensorFlow. Let’s move on to OpenCV.

Installing OpenCV

TensorFlow’s object detection examples typically use matplotlib to display images, but OpenCV is preferred because it’s easier to use and less error-prone. The object detection scripts in the GitHub repository in this guide use OpenCV. To make OpenCV work on the Raspberry Pi, many dependencies need to be installed via apt-get.

sudo apt-get install libjpeg-dev libtiff5-dev libjasper-dev libpng12-dev 
sudo apt-get install libavcodec-dev libavformat-dev libswscale-dev libv4l-dev 
sudo apt-get install libxvidcore-dev libx264-dev 
sudo apt-get install qt4-dev-tools libatlas-base-dev
sudo pip3 install opencv-python

If all went well, OpenCV is installed on your Raspberry.

You can check if the installation is successful and the installed version. Open a terminal and launch the Python3 interpreter.

The TensorFlow object detection API uses Protobuf, a package that implements Google’s Protocol Buffer data format. Before, you had to compile the Protobuf source code (a bit tedious), but now the installation is very simple, thanks to the multiple contributions of the community.

sudo apt-get install protobuf-compiler

In order to check the version installed, run the command:

protoc --version

You should have in response libprotoc v3.20.0 (latest version.)
Create a TensorFlow directory and navigate to it (/home/pi/tensorflow).

mkdir tensorflow
cd tensorflow

Download the TensorFlow repository from GitHub by typing:

git clone --depth 1 https://github.com/tensorflow/models.git

Next, you need to modify the PYTHONPATH environment variable to point to certain directories in the TensorFlow repository you just downloaded. PYTHONPATH needs to be set each time a terminal is opened, so the .bashrc file needs to be edited.

sudo nano ~/.bashrc

Go to the end of the file, and add this line:

export PYTHONPATH=$PYTHONPATH:/home/pi/tensorflow/models/research:/home/pi/tensorflow/models/research/slim

Now we need to use protoc to compile the Protocol Buffer (.proto) files used by the Object Detection API. The .proto files are in /research/object_detection/protos, but we need to run the command from the /research directory.

cd /home/pi/tensorflow1/models/research
protoc object_detection/protos/*.proto --python_out=.

Next, move into the object_detection directory:

cd /home/pi/tensorflow/models/research/object_detection

Now download the SSD_Lite model. Google teams have developed a series of pre-trained object detection files, with varying levels of speed and accuracy. The Raspberry Pi has a relatively weak processor for the recognition application, so a model should be used that takes less processing power. Here we will use SSDLite-MobileNet, which remains well suited for our Raspberry Pi. Download the file and unzip it into the object_detection directory.

wget http://download.tensorflow.org/models/object_detection/ssdlite_mobilenet_v2_coco_2018_05_09.tar.gz
tar -xzvf ssdlite_mobilenet_v2_coco_2018_05_09.tar.gz

Finally, copy/paste the python program from this Github link in a file named Object_detection_picamera.py

If you want to port the application to other Raspberry Pi with OpenCV and TensorFlow installed, simply download the .ZIP of the necessary files available on GitHub.

Your application is now ready to work!


Once your application is operational, all possibilities are open. For an autonomous application, based on solar panels, it would suffice to perform a calculation of the power consumed by the entire installation, and to determine the appropriate type of battery.

Still at the battery level, the Lion-i technology seems well suited, because of its small size and its autonomy, the price is higher than a lead battery, but offers good results in an environment subject to cold or heat. heat.

The top 10 technologies to follow in 2022

Top 10 technologies in 2022

The leading technology advisory and investment firm specializing in technologies, GP Bullhound, has published its annual report concerning its tech predictions for 2022. We are presenting in this post the top 10 technologies that you must follow in 2022. These technologies could literally influence and change your life. for other articles, you can visit this link.

2021 has seen record growth in global technology M&A activity, driven by the need for companies to remain competitive and innovative. Companies are also rethinking their supply chains due to changing geopolitical relations, trade wars and environmental concerns. As consumers adopt new buying habits. These phenomena give rise to technological trends, which attract investment.

Content creators are becoming more popular

Content creating

Globally, there are approximately 50 million influencers on YouTube, Instagram, Twitch… Estimated at 50 million worldwide, they have contributed to the emergence of a new economy. An economy that is based on the monetization of their own content offered to their fans. through different channels. Unlike employees, they are not subject to a standard 9-5 working day to obtain correct remuneration.

An Inzpire.me study shows that Instagram influencers only need 42,575 subscribers to earn the equivalent of an average salary in the United Kingdom (39,000 euros) by creating only eight publications and eight stories per month. . In the United States, the best influencers can earn more than 420 times the average annual income of Americans (107,000 euros). At the same time, many micro-influencers (10,000 to 50,000 subscribers on social networks) develop their online presence alongside their jobs.

Why is this sector going to grow? Influencers have a better understanding of their fans and the content they like, which drives brand interest. In addition, they will be able to develop their economic strategy on several different channels via NFTs for example. The artist Beeple has thus sold a work of digital art for 69 million dollars at Christies.

Supply chain: software is becoming essential

Supply chain and software

The Covid-19 pandemic has severely affected global supply chains. Despite the reopening of borders and the end of confinements, companies are struggling to restore inventory levels before the pandemic. Idling factories – especially in Asian countries – and growing global demand have saturated supply chains. To fill these gaps, companies are increasingly using software that allows them to detect potential problems upstream and facilitate the optimization of raw material supply.

The Metaverse: how close are we?


The metaverse is the new big project of Facebook, which has already won the favor of the public administration of Seoul. The ambition of these new spaces is to change the way people interact. They meet there, work and play using virtual reality headsets, augmented reality glasses, apps, etc. The business opportunities offered by the metaverse, particularly in marketing, will lead to the emergence of new industries. Some companies are already promising to launch a product by 2023. Retail is the most interested sector in these solutions to offer its customers the chance to virtually try on clothes. It is only a small step to see this same proposal arrive in the metaverse according to GP Bullhound.

For their part, Facebook and Microsoft are already working on the first versions of the metaverse. The functionalities offered today by virtual reality and augmented reality will evolve to adapt to consumer demand. This development will go through the integration of NFTs in the form of clothing or art objects.

AI: a driver of diversity

AI: a driver of diversity

The startup and tech ecosystem is struggling to truly address the issue of diversity and inclusion. For GP Bullhound, algorithms and artificial intelligence could improve the fairness of recruitment and create more opportunities for marginalized candidates.

Companies like Entelo internally train artificial intelligence models to detect underrepresented candidates and predict underlying skills. Data will also allow companies to understand the biases that prevent them from recruiting these talents. But this is only the first step. Companies will have to work on their culture and the inclusion of these diversities. Hopefully, this will give them all the possibilities to evolve and to increase their skills on interesting projects.

Wearables and AI go hand in hand

Wearables and AI

Manufacturers of connected wearables accessories (watches, textiles, glasses, etc.), are no longer content to develop objects but are beginning to invest in powerful artificial intelligence engines to generate and use data. Using AI-powered software, these companies can now provide granular data analytics and even produce predictive analytics on health, physical performance and more to their users. The growth of this market is made possible by familiarizing consumers with these objects and monitoring their health on a daily basis. But if they adopt these solutions, they nevertheless remain cautious about sharing their data and are worried about the multiplication of hacks.

At the moment, half of the market is in the hands of the giants, Apple, Samsung, Huawei and Xiaomi. in order to meet the aspirations of consumers, Companies are developing new solutions in various sectors such as finance or health. The global IoT analytics market may reach $59 billion by 2021.

Semiconductors is pushing companies to adapt

Semiconductors & companies

For several months now, companies have been facing a shortage of semiconductors that are pushing them to modify some of their products, particularly in the automotive sector. The main factor for this disruption is the closure of production facilities for chips and semiconductors.

To overcome this lack, software publishers are adapting. Tesla, for example, modified some of its software to accommodate alternative chips. States are also taking up the subject. In the United States, President Biden presented an infrastructure plan including a $50 billion package to expand national chipmaking capacity. In the European Union, lawmakers are scrambling to pass a law to uphold “technological sovereignty” aimed at increasing the volume of chips developed in Europe. Taiwan’s TSMC, the world’s largest chipmaker, has pledged $100 billion over the next three years to ramp up production.

Buy now, pay later (BNPL)

Buy now, pay later

The “Buy Now Pay Later” (BNPL) solution is beginning to have a lasting impact on the e-commerce and payment sector due to growing consumer adoption. GP Bullhound even talks about abandoning the bank card in favor of the BNPL, which avoids overdraft fees and the costs associated with taking out credit.

This solution is of particular interest to younger generations since 26% of Millennials and Gen Z already use BNPL plans for their purchases. Affirm, one of BNPL’s leading service providers, has shown that merchants adopting its solution have seen an average of 85% increase in order size. Specialists are expecting this trend to continue as small businesses transition to omnichannel. 68% of them already believe that BNPL plans facilitate sales.

The e-commerce and tech giants did not hesitate for long to enter this niche. In 2021, Square acquired Afterpay, Amazon partnered with Affirm, and Apple announced it would provide its own BNPL products. BNPL’s global spending is expected to reach $995 billion and the number of users to exceed 1.5 billion by 2026, up from 266 billion and 340 million respectively in 2021.

Decentralized finance


Decentralized finance (DeFi) is booming after two years of astonishing growth. The value of cryptocurrencies deposited as collateral increased 14 times in the past year, surpassing $1 billion in June 2020. The rapid pace of compliance innovation is driving wider adoption by institutions, and soon by the general public, which remains at an early stage compared to the wider crypto industry. At the time of writing, over $100 billion is now locked in DeFi protocols on the Ethereum blockchain on which most DeFi applications are built.

By allowing anyone to create protocols that replicate existing financial services using public blockchains and smart contracts, platforms like Ethereum enable secure, permissionless, and middleman-free financial transactions.

These decentralized financial applications – which touch the entire financial value chain – are redefining traditional financial services and offering unprecedented levels of global transparency, interoperability and equal access.
These new technologies, like NFTs, will face many adoption, evolution, governance and regulatory challenges.

ARM replaces the Intel chips

ARM replaces the Intel chips

For decades, the use of ARM processors was limited to mobile devices. Now, their efficiency and versatility have distinct advantages for machine learning applications. Another advantage is the possibility of deploying them in mobile or desktop devices.

Given the versatility and power efficiency of ARM processors, applications span the entire range of IoT devices. ARM-powered devices will be able to run advanced artificial intelligence algorithms to process more data and make better inferences. Their use has been mostly limited to enhancing smartphone functions, such as facial recognition, fingerprint scanning, and voice-activated commands. Future uses could make autonomous vehicles safer, improve the functionality of wearable medical devices, and more.

A growing number of companies are migrating their devices to ARM processors. Some of theme are choosing to develop their own competing processors. For example, the Apple’s M1 chip included in the latest MacBook Pro. Google and Microsoft are also developing their own ARM-based processors for use in personal devices and cloud servers. By developing their own processors, tech companies can more effectively implement artificial intelligence algorithms in their products. With time and its adoption by more and more companies, new software will be cheaper and easier to develop.

Artificial intelligence and healthcare

artificial intelligence and healthcare

The Covid-19 pandemic has allowed remote assistance and telemedicine solutions to really take off by breaking down many barriers. As a result, the confidence of consumers and doctors has increased in new technologies dedicated to health. For instance, the number of patients that uses remote care increased by 15 to 20% since the start of the pandemic. The early success of these AI-based practices will drive investment and resources to further develop new solutions.

Software will help shape the future of medicine. Data analysis by artificial intelligence will continue to develop to become a real diagnostic and prediction aid tool. Asynchronous solutions using artificial intelligence in the form of software and hardware platforms offer obvious advantages through their ability of being remotely used. The capabilities of these solutions are fundamentally changing the way healthcare is delivered remotely.