RK, the Turkish Competition Authority, which is a government agency regulating competitive market processes, fined Meta Platforms for violating the country’s competition law. The fine is 346.72 million liras, equal to 18.63 million US dollars.
According to RK, combining the data collected from Facebook, Instagram, and WhatsApp services caused the deterioration of competition which made it difficult for Meta’s competitors operating in online display advertising markets by creating barriers to enter the market.
The RK said that Meta breached the Turkish competition law’s article 6. However, Meta can appeal the decision at the Administrative Court of Ankara within next 60 days. A company spokesperson said that Meta has disputed the decision of Turkey’s RK.
The spokesperson said Meta Platforms strive to protect user privacy and give people transparency and control over their personal data. They further added that the company will consider all options.
Following a new privacy agreement in 2021 that asks WhatsApp users to share data with Facebook, Turkey launched an inverstigation into WhatsApp and Facebook. Meta had to put a stop to the new privacy agreement in light of the reactions and the investigation.
Turkey also occasionally fines social media giants, including Meta platforms, for defying the regulations and laws that aim to increase government controls. Social media platforms were focused on in Turkey after the government passed a new disinformation law on October 14 that will maximize the control of Turkish government on social media platforms.
Blockchain is a distributed, decentralized ledger (or database) used to store information electronically in a list of ordered records known as “blocks.” These blocks are shared across multiple computers via cryptography. Each block contains a cryptograph hash (a function that converts input data into fixed-size output), timestamp, and transaction data related to the previous block. The chain of blocks records transactions securely and protects against changes or alterations. Blockchain technology is gaining popularity in real estate, insurance, E-voting, government benefits, artist royalties, etc.
Free Blockchain Courses
There are several resources available using which you can learn more about the technology. Some potent and free Blockchain Courses have been mentioned below.
Blockchain Basics by Great Learning
Blockchain Basics is a beginner-level course developed by Great learning that aims to empower newcomers with robust blockchain fundamentals. Initially, you will learn about essential concepts like cryptography, consensus mechanism, transaction mechanisms, etc. The course also features a blockchain ecosystem and its adoption process in industries. The course comprises real-world examples to make it more realistic and practical for the students.
After understanding the basics, if you wish to advance your skills in Blockchain and IoT, you can check out a comprehensive course on Advanced Software Engineering for Blockchain hosted by IIT Madras in collaboration with Great Learning.
YouTube is an excellent source for learning without paying vast sums of money. Even when it comes to learning such complex technological topics as blockchain, there are several short courses that you can find on YouTube. This YouTube video provides 3-4 hours of accessible course material discussing blockchain’s basics. The entire video tutorial is divided into three parts; the first describes blockchain, the second talks about the applications, and the third shows how it works. You will also learn about NFTs (non-fungible tokens), Web3 (a new iteration of WWW or the World Wide Web), smart contracts in Ethereum, and the blockchain metaverse.
After gaining a basic understanding of blockchain, you can proceed with more advanced courses that give you a real-world perspective on the technology. This free crash course will acquaint you with blockchain’s impact on your business with real-world examples from famous corporate practitioners’ interviews. The course’s primary objective is to empower entrepreneurs with all the necessary learning materials and resources to capitalize on business opportunities.
It will be an excellent place to start your blockchain journey if you want to gain valuable knowledge and revolutionize your business ecosystem.
Decentralized cryptocurrencies are gaining popularity lately, and most of it is credited to the use of blockchain. Blockchain technology features distribution and decentralization capabilities extensively applied in the cryptocurrency market. In this free online course, you will learn about the fundamental concepts of blockchain and its applications in Bitcoin. The course initially talks about the factors that reason in favor of blockchain technology. It discusses the benefits of Bitcoin as a cryptocurrency, its requisites, exchanges, wallets, and much more. The course provides a detailed explanation of the inner workings and guiding principles.
If you are interested in cryptocurrencies, you can start your journey by gaining a valuable understanding of what they are and how they work.
This free online course on edX is specially designed for developers who want to learn about blockchain technology. It is developed at Berkeley in conjunction with experts from the Computer Science Department. In this course, you will learn about blockchain foundations with a mathematical approach. It covers topics like the CAP theorem, the Byzantine Generals problem, and many other mathematical concepts. The course also provides an overview of Bitcoin and its application of Blockchain. Toward the end of this course, you will learn about several enterprise-level implementations by companies like JP Morgan, Tendermint, and HyperLedger.
Introduction to Digital Currencies and Blockchain MOOC
This free blockchain program by the University of Nicosia is the first M.Sc course in digital currencies and blockchain technology. The MOOC (massive open online course) is taught by experts like Andreas Antonopoulos, Antonis Polemitis, and George Giaglis. It is a great place to start if you are interested in learning the technical overview of decentralized digital currencies like Bitcoin. Students will get hands-on experience with how blockchain works in the provision of financial services. Additionally, they will get credits for clearing mandatory graded activities along with the concluding essay-based examination.
One of the most popular blockchain applications is Ethereum technology, a computing platform where developers can create and deploy applications decentrally. This course is developed at Berkeley under the guidance of leaders from Blockchain startups like Consensys, Virtue Poker, and BlockApps. The free course will teach Blockchain by helping you create a Hello World Blockchain Application within four modules.
The course is ideal for developers interested in DApps (decentralized apps) and seeking in-depth knowledge of the process. College students, practicing developers, or individuals interested in solidity concepts should try this free blockchain course.
Blockchain and FinTech: Basics, Applications, and Limitations.
Blockchain technology grew in tandem with Bitcoin and now forms the core of several other FinTechs. Today, many companies utilize blockchain for multiple applications in finance, logistics, insurance, etc. However, it is not easy to understand how to incorporate the technology. To get a clear picture of applications, this course aims to provide a general overview of the technical details and limitations of applying blockchain across your fintech application. In conclusion, the course will also brief you on the downsides of this technology in providing security against criminal activities. The course was developed and led by Professor Siu Ming Yiu at the University of Hong Kong.
Coursera is an online platform that offers online courses with a vision of providing “”life-transforming” learning experiences. Coursera has a full-fledged course on Blockchain Specialization that gives students a broad idea of essential blockchain concepts. This specialization comprises many sub-courses, some of which are:
Blockchain Basics by Coursera
The University of Buffalo and The State University of New York have developed this course to include hashing techniques and cryptography foundations that form the foundation of blockchain programming. The course begins with defining blockchain and moves forward to Ethereum Blockchain as an application of the technology. You will also learn about the algorithms and techniques behind asymmetric key encryption, hashing, etc.
Blockchain Platforms is the fourth block of the Blockchain Specialization offered by Coursera. The course provides learners with a basic knowledge of a blockchain ecosystem on several platforms. You will learn about two detailed decentralized applications, Augur and Grid+. These applications will use Hyperledger blockchain architectures and service models to analyze the decentralized apps while discussing their privacy and scalability challenges. This course will thus help you to advance your blockchain knowledge in solving real-world problems. Here is the link to sign up- Blockchain Platforms
Adobe MAX recently announced its approach to developing creator-centric Generative AI offerings using Content Authenticity Initiative standards. The company is also investing in new research to enhance creatives’ control over their work and style.
This transformational technology accelerates how artists brainstorm and explore creative avenues. It enhances the accessibility of creativity. The CAI is Adobe’s initiative, with over 800 partners working to increase trust online. CAI’s open-source technology securely lets creators attach provenance data to digital content.
According to Adobe researchers, Generative AI is a hyper-competent creative assistant that can multiply what creators can achieve by presenting alternative approaches and new images without losing the essence of human imagination. Adobe is taking a step by investing its research and product design talent to formulate an approach that revolves around the needs of creatives by incorporating Generative AI in Adobe creative tools.
The research is still at a nascent stage. According to Adobe, AI within Photoshops generates rich, editable PSDs. The AI can generate a plethora of approaches, and the creator can pick two or three they want to explore using Photoshop’s wide selection of tools to transform the AI-generated image based on the artist’s creative perspective.
Generative AI in Adobe Express will aid inexperienced creators in achieving their unique goals. For example, rather than finding a premade template to start a project, the users could generate a template through a prompt and leverage Generative AI to put an object on the scene or create a unique test effect based on their description.
The artist will still have complete control. They can use Adobe Express tools to edit images, change solos, and add fonts to create the flyer, poster, or social media post they imagine.
Facial recognition has become a part of our daily life in mobile phones, computers, biometrics, and more, providing a sense of personal security. Computer vision is the new age of technology that powers facial recognition and sometimes outperforms humans in the facial recognition solution of face detection, analysis, and recognition. The algorithms use computer vision techniques to map, examine, and verify to identify a face in a picture or a video. Thereby, we rely on facial recognition along with biometrics greatly for information security, access control, and surveillance systems. According to Allied Market Research, the global facial recognition market has been increasing since the COVID-19 pandemic and is predicted to reach $16.74 billion by 2030 at CAGR of 16.0%. This will lead to significant advancements in computer vision, particularly for facial recognition, and the idea to pursue a profession in computer vision is a good idea, or learn computer vision out of curiosity. You can practice model building using the listed facial recognition datasets to get started.
1. Flickr Faces HQ (FFHQ) Dataset
Flickr Faces HQ dataset is a high-quality image dataset of human faces created in 2019 as a benchmark for generative adversarial networks (GAN) in the research paper “A Style-Based Generator Architecture for Generative Adversarial Networks” by Tero Karras, Samuli Laine, and Timo Aila. This facial recognition dataset comprises 70,000 high-quality PNG images at 1024×1024 resolution and has age, ethnicity, and image background variations. The images collected in this dataset are crawled from Flickr, an American image hosting and video hosting service. To note, under NVIDIA Research Licensing, the dataset is not intended to be used in any development or improvement of facial recognition projects and technologies.
Tufts Face dataset is a comprehensive and large-scale facial recognition dataset containing over 10,000 images and have seven image modalities, including visible, near-infrared, thermal, computerized sketch, LYTRO, recorded video, and 3D images. The Tufts Face dataset collected images from more than 15 countries, of which 74 are females, 38 are males and an age range from 4 to 70 years. The dataset was created in 2019 and made available to researchers worldwide to use for non-commercial and educational purposes benchmarking facial recognition algorithms such as sketches, thermal, NIR (near-infrared), 3D face recognition, and heterogamous face recognition.
The Real and Fake Face Detection dataset is a face dataset created by Computer Intelligence and Photography Lab at Yonsei University in 2019. The dataset is well known for its high-quality photoshopped fake face images generated by experts. The collection of real and fake face images are put in separate files under the parent directory as training_real and training_fake files and contains around 1000+ real face images and 900 fake face images. The images in the Real and Fake Face Detection dataset vary for different face sizes and the features of the eyes, nose, mouth, and whole face. Also, the fake face images have a label for recognizable difficulty ranging from easy, mid, and hard.
Multi-Attribute Labelled Faces dataset is the first face dataset supporting fine-grain evaluation of face detection in the wild. The dataset contains 5,250 images with 11,931 labelled faces collected from the internet and introduced in 2015 in the paper “Fine-grained Evaluation on Face Detection in the Wild” by Zhen Lei, Bin Yang, Junjie Yan, and Stan Z.Li at the Chinese Academy of Sciences. The dataset has two main features that the annotations or labels of multiple facial attributes make it possible for fine-grained performance analysis, and it reveals the true performance of algorithms in practice.
Wider Face dataset is one of the biggest large-scale face detection benchmark datasets containing rich annotations, including poses, event categories, face bounding boxes, and more. The dataset was created in 2018 by the Multimedia laboratory at the Chinese University of Hong Kong. The Wider face dataset contains 32,203 images and labels 393,703 faces with scale, pose, and occlusion variety. Additionally, the dataset follows an event class-based organization with 61 event classes, and for each event class, random sets are selected in the ratio of 40%/10%/50% for training, validation, and testing.
6. Face Detection Dataset and Benchmark (FDDB) Dataset
Face Detection Dataset and Benchmark dataset is a facial recognition dataset designed to study the problem of unconstrained face detection. The dataset was created by the Department of computer science at the University of Massachusetts Amherst and introduced in the paper, “FDDB: A Benchmark for Face Detection in Unconstrained Settings.” This dataset contains 2845 images from the Labelled Faces in the Wild dataset, with annotations for 5171 faces. FDDB can be challenging to work with as it includes difficult pose angles, out-of-focus faces, low-resolution images as the resolutions of images varies greatly, and greyscale and color images.
Google Facial Expression Comparison dataset is a facial recognition dataset created and introduced by Raviteja Vemulapalli and Aseem Agarwala, Research scientists at Google. This is a large-scale facial expression dataset with face image triplets and human annotations specifying which two faces show the most similar expression. It contains more than 156k face images with 500k triplets. The dataset is intended for researchers who are interested in facial expression analysis, including emotion classification, expression synthesis, and more expression-based analysis. It was published in 2018 and focuses primarily on discrete emotion classification or action unit detection than plane old face expression datasets.
8. Face Images with Marked Landmark Points Dataset
Face Images with Marked Landmark Points dataset is a facial recognition dataset containing 7049 images with up to 15 key points. This dataset is a primary face dataset that can be used as a building block in various face recognition projects like tracking faces in images and videos, detecting dysmorphic facial signs for medical diagnosis and biometrics, and so on. The dataset was published in 2018 by Kaggle and was provided by Dr. Yoshua Bengio of the University of Montreal.
Labelled Faced in the Wild dataset is one of the most popular facial recognition datasets. The dataset is a public benchmark for face verification, also called pair matching, containing web images of 13233 images of 5749 people and 1680 people with two or more images. LFW was published in 2018 by the University of Massachusetts and was designed to study the problem of unconstrained face recognition. This dataset provides information for supervised learning with image-restricted and unrestricted training modules. Also, the modeling results using the LFW dataset are promising. To date, 123 models have been applied to the dataset, and the results have been publicly released on the website.
YouTube Faces with facial key points is a processed version of the YouTube Faces Dataset, a collection of short videos of celebrities downloaded from YouTube. The dataset comprises around 1293 videos with up to 240 frames for each video and 155,560 single image frames. It was created and uploaded by Dr. Guillermo on Kaggle, the inspiration came from the Face Images with Marked Landmark Points and was intended for facial recognition across videos. The dataset can be used for test transfer learning between other face datasets, other face recognition projects like animal face detection, and many more.
CelebFaces Attributes dataset is a large-scale face attributes dataset having more than 200k+ celebrity images each with 40 attributes. The diversity of images in CelebA is vast, the dataset comprises 10,177 identities and five landmark locations, and rich annotations. CelebA can be used in many facial recognition projects, including face classification, face detection, face editing and synthesis, face localization, and so on. The dataset was released in 2015 by Multimedia Lab at the Chinese University of Hong Kong for non-commercial research purposes. The CelebA dataset was used in the paper “Deep Learning Face Attributes in the Wild,” which may provide more insight into the dataset.
The iQIYI-VID dataset is the largest in size among this list of facial recognition datasets due to the presence of face videos. The face videos make it unique and challenging to handle compared to other facial recognition datasets. It is a large-scale dataset for multi-modal person identification comprising 600k videos of 5,000 celebrities collected from the website iQIYI, a Chinese online video platform. All the clips in the dataset pass through a careful human annotation process, and the error rate of labels to be lower than 0.2% is considered a part of it. The dataset was introduced in the paper “iQIYI-VID: A Large Dataset for Multi-modal Person Identification” by iQIYI Incorporation. The dataset is not available yet but will soon be public.
In this article, we want to share thoughts about project management homework and how to make it more effective and quick.
Before we start, let’s discuss the main components of project management’s (PM) responsibilities. The PM should use the existing resources to lead the client’s ideas to successful implementation. To make it real, the manager should make a plan, organize a team of specialists, structure the work process, create feedback loops between the team and a client, and react to all moments that negatively influence the project implementation.
Your project management course may contain assignments that are directly related to your future profession. For example, students are typically asked to compose project documents, risk analysis, create project plans, and more. If it is difficult to do a project management assignment, you can always ask for project management homework help. When you get expert help, you will have the possibility to clarify all points that you can’t understand and implement new knowledge in new projects.
So, is it hard to do your project management homework tasks independently? The answer is yes and no. Here are the tips that can help you while doing project management assignments.
9 Tips to Do Project Management Homework with Ease
1. Make up your workspace.
First things first, take care of the environment you will be working in. The area should be silent and clean to boost your concentration and performance. Ask your roommates, partner, or family members to keep quiet. Make sure that your table contains only important things like a laptop, notes, and a pencil. Besides, you can take some snacks and a cup of drink to avoid heading to the kitchen to find something tasty. If you want to do the project homework faster, you will need to focus totally on the work.
2. Read the assignment carefully.
A project manager’s good quality is taking notes of the details, paying attention, and concentrating on the task. One assignment may ask you to draw Gants and PERT charts, create a report, make a feasibility study, or just answer a list of questions. What does the teacher want to see in your homework? What are the key elements? Do you have all the needed information? What stages do you need to overcome? Write down the list of required actions to do.
3. Come up with the idea.
Typically, teachers provide you with a case study or a project concept that you need to carefully read and imagine yourself in the role of project manager. A project management process is tied directly to major points of what should be done. If your homework is to create a project plan, you need to define the project scope, key objectives, and a team of executors. Make a list of questions you need to ask the high management to clarify some moments.
4. Read out the instructions.
If you need to do your project in a specific program, make sure that you follow your teacher’s guidelines or specific instructions. Also, guidelines are very helpful when you need to create a more solid project management assignment or report. A step-by-step guide will help you not to lose track of your work and organize your essay in a logical structure.
5. Plan your time.
You may need sufficient time to complete a list of project management tasks and solve managerial problems. Studies will take more or less time and depend on your abilities and the scope of the problem. Make sure that you have left enough time before the deadline to do your homework on time.
6. Conduct research.
Look through your textbook and class notes for more information on the project. Find out whether your teacher has given you a list of recommended sources where you can find information about project management methodologies and project management tools. You may need to find additional information, statistics, and other data to make your project management homework. Find supporting evidence and facts to make your work look credible and professional. Find journals and blogs related to project management and look through current information on management issues and tools. Make sure that the found sources are credible.
7. Ask someone for help.
If you can’t handle the project management assignment, you can speak to your teacher or other students involved in similar projects for clarification. Consider the fact that your teacher won’t give you direct recommendations or point out your mistakes. You will get general tips or a reminder of what you have already learned in class. If you need more clarifications, you can search for online help with project management homework and ask experts to assist you with specific project management problems. It’s a quick way to get prompt and complete answers to all your tasks and questions. When you see how something should be done, you can use your knowledge in future projects.
8. Properly organize your work.
Sometimes the assignment may require you to format the text into tables, diagrams, decision trees, or management reports in the appropriate format. Moreover, the information may be presented on video or digital media.
Make calculations if needed. For example, you may be asked to calculate probability in %, estimate the cost for each task, KPI indexes, project costs, and other key numbers. Don’t forget to support your numbers with explanations. Check whether you need to create a title page, table of contents, and works cited list.
9. Revise and finalize your work.
When you have finished all calculations and comments, look it through. Fix all grammar and punctuation mistakes, and check whether your calculations are correct. A good project manager should be attentive to details and always ensure that mistakes are eliminated. Moreover, such a checkup will help you find the gaps in your research or find something that may be improved or changed.
Summary
Project management homework may be challenging, especially when you need to create a big multi-level project. All the skills you will get after completing numerous project management assignments will help you understand the project life cycle, be able to plan projects, execute the project, and carry out project evaluations.
Meta Quest Pro, Meta’s advanced mixed-reality headset, is now available for US$1,499.99. The headset was announced at Meta Connect 2022 with cutting-edge features that enable users to have a mixed-reality experience.
Meta Quest Pro is a potent device for collaboration and working closely and naturally with developers located at different locations using virtual reality. The headsets come with pancake optics, advanced LCD for sharp visuals, eyes, and natural facial expression tracking, all in a versatile design. It offers a guided Fit Adjustment to make it convenient for the users to carry it for longer durations.
The headset comes with two self-tracking Touch Pro controllers, partial light blockers, a charging clock, and stylus tips. It can be purchased from the company website and at select retailers where Meta Quest products are supported.
Meta aims to develop and improve a rich ecosystem of experiences by leveraging Meta’s social presence capabilities and plans to continue working on improvising the technology to enhance the consumer experience.
Meta releases EnCodec, a neural network trained to reconstruct input audio signals into smaller files. Meta researchers claim to receive state-of-the-art results in low-bit-rate audio hypercompression.
Encodec, our AI-powered compression neural net, has 3 parts: 1️⃣ Encoder: transforms raw data into higher dimensional + lower frame rate 2️⃣ Quantizer: compresses to target size, equiv. to mp3 3️⃣ Decoder: turns compressed signal back to waveform, most similar to the original
EnCodec has a streaming encoder-decoder architecture that utilizes sequential modeling. Such convolutional-based encoder-decoder architectures are very potent in multiple audio-based jobs, like audio enhancement, audio bandwidth extension, audio separation, and many others.
EnCodec comes with three main components, Encoder, Quantizer, and Decoder. The Encoder network (E) transforms input audio into a latent representation (z) with a higher dimension and lower frame rate. Then the Quantizer (Q) compresses it to the desired target size in an MP3 format and outputs z𝔮. Finally, the Decoder network (G) transforms the compressed audio signal into a waveform (ẋ), nearly similar to the original one.
Meta researchers claim to have achieved a 10x compression rate vs MP3 at 64kbps without compromising audio quality. It is a pioneer research as this is the first time a 48kHz stereo audio was used as an input. Meta released a research paper highlighting all the technical details and architecture behind EnCodec. The paper also highlights that a Transformer model of EnCodec can be used to make it more efficient and reduce audio bandwidth by 40% without any quality loss. To help developers and people with a technical background to understand more about EnCodec, Meta has also released the code.
According to the new prime minister of the UK, Rishi Sunak, the G7 is launching a set of policy principles for Central Bank Digital Currencies (CBDCs). The UK is a member of the G7 along with Canada, France, Germany, Italy, the United States, and Japan.
Recently, Rishi Sunak was elected as the new Prime Minister of the UK. Sunak has been pushing the country to support cryptocurrency. He was vocal about the same while serving as Chancellor of the Exchequer.
Sunak issued support and a renewed focus on the cryptocurrency sector on Monday. Sunak said governments and central banks would work together on a potential digital currency issued by a central bank. Key priorities are having a secure transaction that can offer other ways to pay, is energy efficient, and is available to everyone, Sunak added.
Sunak added that he had announced a joint task force for the UK Treasury and Bank of England to look into the CBDCs earlier this year. He said the decision on CBDCs is in the exploratory stages.
Sunak called the exploration a critical step in support of cryptocurrency and working with international partners. He said, “We’re excited to be taking a leading role with G7 members in publishing this exploratory work, bringing money and finance into the 21st century.”
Photo licensing service Shutterstock will begin selling images generated by artificial intelligence along with those created by humans. The AI-generated images will be powered by OpenAI’s DALL-E 2 software exclusively. According to both companies, human creators whose work inspired the AI will be compensated.
Shutterstock began removing AI-generated art from its archives last month. A Shutterstock spokesperson said that the company would keep banning people generally from uploading AI-generated art to its platform. They added that its collaboration with OpenAI was an attempt to adopt new technology ethically.
The two companies also plan to launch what the Shutterstock spokesperson called the Shutterstock Contributor Fund to compensate artists for their contributions and provide royalties when their intellectual property (IP) is used.
OpenAI didn’t respond to a request for comment. Shutterstock spokesperson said that a deal had been struck in which the AI that produces the pictures was trained only on images from Shutterstock’s archives rather than online content.
According to the Shutterstock spokesperson, contributors whose work was used to train the models will receive a share of royalties from AI sales. Still, they didn’t say what percentage of revenue would go to contributors or how the contributions would be divided. It is often difficult to determine what input data was referenced to create any one piece of output.
Adrian Alexander Medina, the editor of the literary website and magazine Aphotic Realm and a creator of book covers, says he has lost three potential clients to AI-generated art since October. He disagrees with Shutterstock selling AI-generated art and believes it risks ostracizing photographers and illustrators.
Every year, the Indian technology market expands, increasing its desire for new smartphones, smart TVs, and PCs. Semiconductors play a crucial part in all the electrical devices we use because they control the flow of electricity, which powers devices. The pandemic caused a sharp fall in semiconductor chip output, which sped up and increased the demand for semiconductors in India. For that cause, several semiconductor companies in Bangalore are at peak production and planning for innovations. For a decade or more, Bangalore has been the technology hub for curious minds, so it is known as the Silicon Valley of India and is home to some best VLSI (very large-scale integration) industries. Here is the list of top semiconductor manufacturer companies in Bangalore.
1. Qualcomm
Qualcomm is an American multinational corporation founded in 1985 under the idea of “QUALity COMMunications,” from which the name has been derived. The company is based in San Diego, California, and incorporated in Delaware, which stands as one of the most popular processor manufacturing companies in the mobile industry. Qualcomm is a provider of semiconductors, software, and wireless technology. Additionally, the company produces software components for automobiles, computers, cell phones, watches, and many other electronic devices. Qualcomm developed the code division multiple access (CDMA) in 1995, which changed wireless communications forever and is the foundation for all 3G networks that also helps to define the latest 4G and 5G technologies. Over the years, the company has used a fabless manufacturing strategy to commercialize semiconductor components and provides powerful connectivity solutions, including patents for 4G, 5G, TD-SCDMA, CDMA2000, and WCDMA mobile communication protocols. Qualcomm India office is set up in Banglore, Karnataka, which is in top semiconductor companies in Banglore, intending to make mobile communications affordable and accessible to all.
2. ASM Technologies
ASM Technologies Ltd is an Indian technological solution provider headquartered in Banglore, India, established in 1992. It is one of the top semiconductor companies in Bangalore, with global offices in the USA, Singapore, the UK, Mexico, Japan, and Canada. The company works in the areas of engineering services and product R&D (research and development) by offering innovative solutions with development and support centers in India and overseas. ASM Technologies’ vision is “To be a global leader, committed to the customer in providing the technology solutions with the highest degree of excellence, quality and value by an agile team and efficient process.” The company has nurtured a successful business in consulting and product development services for over two decades and wishes to do more in the future.
3. IBM
IBM (International business machines) Corporation is an American multinational technology based in Armonk, New York, and operates in over 171 countries, including 12 facilities in different cities in India. The company was founded in 1911 by businessman Charles Ranlett Flint under the name Computing-Tabulating-Recoding Company (CTR), and later in 1924, it was changed to IBM. IBM primarily works in producing and selling computer hardware, middleware, and software and delivers hosting and consulting services in mainframe computers, nanotechnology, and more. Additionally, the company offers a range of semiconductor technologies, products, and services in product R&D, supply chain and marketing, sales, and services. It has been one of the best semiconductor companies in Banglore since 2006, when IBM first set up its office in India. IBM has a legacy of leadership in semiconductor research delivering smaller, faster, and more reliable semiconductor devices. Currently, IBM and its industry partners are pushing the limits of chip technology to adapt implementations of cloud computing and AI.
Broadcom Inc. is an American global designer, developer, manufacturer, and supplier of semiconductors and infrastructure software products, which was founded in 1961 and based in San Jose, California. The company is focused on category-leading semiconductor and infrastructure software solutions, which led the company to be one of the technology leaders. Broadcom has established several research and development sites worldwide, including the UK, Frame, Canada, and India. Broadcom India Pvt Ltd was set up in 1997 and currently operates three offices in Bangalore, Hyderabad, and Pune. The company delivers semiconductor and infrastructure software solutions by combining global scale engineering depth, broad product portfolio diversity, superior execution, and operational focus. Additionally, the company helps clients to shape their industry standards to ensure great performance and capabilities with interoperability.
5. Texas Instruments
Texas Instruments Incorporated (TI) is an American multinational technology and semiconductor company that designs, manufactures, tests, and sells analog and embedded processing chips. The company was founded in 1930 and is based in Dallas, Texas, which is one of the top semiconductor companies. Texas Instruments is the pioneer in the transition from vacuum tubes to transistors and integrated circuits (ICs). Though the company has advanced IC technologies, it also provides innovations in each generation to make technology smaller, affordable, more efficient, and reliable, leading the way for semiconductors to go into electronics everywhere. In 1985, TI became the first multinational technology company to establish an R&D center in Bangalore, India, and has been on the list of semiconductor manufacturing companies in Bangalore ever since. The company has developed and delivered over 80,000 products that help customers efficiently manage power, accurately sense and transmit data, and provide core control or processing in electronic systems. TI is powered by the passion for creating a better world by making electronics more affordable through semiconductors and helping customers develop new applications in the industrial and automotive markets.
6. Samsung Semiconductor
Samsung Semiconductor Inc. (SSI) is a daughter company of Samsung Electronics under the Samsung Group, a South Korean multinational manufacturing conglomerate headquartered in Samsung town, Seoul, South Korea. Today, Samsung has a huge brand value in the electronics industry, expanding with highly differentiated mobile devices and working harder to develop next-generation innovation. Samsung Semiconductor was founded in 1983 and is based in San Jose, California, which is advancing as the world’s technology leader in memory, system, LSI, and LCD technologies. The company develops and provides products and technology that industry leaders use in mobile, automotive, AR/VR, gaming, IoT, edge, AI and enables remarkable growth rates in enterprise and hyper-scale data centers. The company established an R&D Institue India-Bangalore (SRI-B), which is the largest center after South Korea and is the key innovation hub in Samsung Group.
7. Tata Elxis
Tata Elxis is a premium engineering service provider around the globe and is one of the prominent leaders in the automotive, media, broadcast, communications, and healthcare industries. It was founded in 1989 based in Bangalore, India’s Silicon Valley, with the mission to foster innovation in the fast-emerging technology and IT market and adopt the cutting-edge technology. Tata Elxis combines advanced technology and user-centric design expertise to deliver innovative solutions for helping customers. The company’s integrated design and technology teams empower enterprises to reimagine their products and services from strategy, consumer research, and insight to service and experience design, integration, launch, and more. Tata Elxis provides some state-of-art products in the fields of AI, broadcast and media, automotive, and healthcare.
NXP Semiconductors is an American-Dutch semiconductor designer and manufacturer company established in 2006 as a Philips semiconductor spin-off. The company provides technology solutions in automotive, industrial, IoT, mobile, and communication infrastructure markets. NXP aims to bring together bright minds to create innovative technologies that connect the world better and make it safer and more secure. NXP invented near-field communication (NFC) with Sony and supplies NFC chip sets for mobile phones used for paying for goods, storing, and exchanging data securely. Also, the company manufactures chips for eGovernment applications like electronic passports, RFID tags and labels, transport and access management with chipsets, and contactless cards for MIFARE (MIkron FARE collection system). NXP has acquired four sites in India, including Noida, Pune, Hyderabad, and Bangalore. NXP Bangalore is an innovation center for the company’s connectivity, security, and advanced analog and radio frequency products.
9. Intel
Intel Corporation is an American multinational technology corporation known as the largest semiconductor chip manufacturer in the world. The company manufactures motherboard chipsets, network interface controllers, integrated circuits, flash memory, graphics chips, embedded processors, and more for communication and computing. Also, Intel supplies microprocessors to big computer system manufacturers like Acer, Lenovo, Dell, and HP. The company was founded in 1968 by Gordon Moore and Robert Noyce, the semiconductor pioneers under the executive leadership and vision of Andrew Grove. With the early developments of SRAM (static random access memory) and DRAM (dynamic random access memory) chips, Intel has shined through other semiconductor companies. Intel established a development center in Bangalore, India, in 1998 and invested over $140 million in 2017 for its upcoming R&D center.
10. Mediatek
Mediatek Incorporation is a Taiwanese fabless semiconductor company that develops innovative system-on-chip (SoC) for mobile, home entertainment, connectivity, and IoT products. It is the world’s 4th largest fabless semiconductor company and one of the prominent semiconductor manufacturing companies in Bangalore, India. The company was founded in 1997 and headquartered in Hsinchu, Taiwan. MediaTek has 25 offices around the world and stands as a market driving force in many key technology areas like power-efficient mobile technologies, automotive solutions, and a wide range of advanced multimedia products, including smartphones, Chromebooks, smart TVs, and voice assistant devices. As the company’s products are in high demand in the Indian market, the MediTek India office was established in Bangalore to strengthen its India presence.
11. Applied Materials
Applied Material is an American corporation providing top-class materials engineering solutions to produce every new chip virtually and advanced display worldwide. The company supplied equipment, services, and software for the production of semiconductor chips for electronics, flat panel displays for computers, smartphones, TVs, and solar panels. Applied Materials excels in modifying materials at atomic levels, which helps customers to transform possibilities into reality at an industrial scale. It was established in 1967 by Michael A. McNeilly and is headquartered in Santa Clara, California. The company operates globally in many locations, including Europe, Japan, North America, Israel, China, Italy, India, Korea, Southeast Ais, and Taiwan. Applied Materials India is the second largest resource for engineering support for Applied globally and one the best semiconductor companies in Bangalore. The office in India provides engineering design, support services, and materials science and engineering innovations through a solid partner ecosystem in India.
