Artificial Intelligence Archives - Page 4 of 10

Yashica Chopra
July 24, 2023
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9 Things Start-up Leaders Should Know About Generative AI

Generative AI uses deep learning algorithms and other technologies to generate output based on the user input. It is an advanced form of general AI capable of handling versatile tasks. Here, we’ll discuss the various aspects startup leaders should know about generative AI to implement the technology in their businesses. Artificial intelligence has been revolutionizing various industries in recent times. Statistics show that the annual AI adoption rate will grow by 37.3% from 2023 to 2030. Artificial intelligence is integral in our personal, social, and professional lives. However, we know that AI is still in the initial stages of exploration. Generative AI is a prime example of this. ChatGPT has changed the way we look at AI. It has created many discussions across the globe. The top companies have been working hard to release their versions of generative AI tools. Other SMBs and multinational organizations are hiring AI consulting firms to understand the importance of generative AI and adopt relevant tools to boost their business. But what is generative AI? What does it do in today’s scenario? How can CEOs and entrepreneurs use generative AI in their businesses? Let’s find the answers to these questions. What is Generative AI, and How Can it Help Your Business? Generative AI is a set of algorithms that can generate new content (text, image, video, audio, etc.) from the training data. The generative AI models are built on models trained using large datasets with unlabeled data. The algorithms learn to self-supervise themselves and identify the underlying patterns. It uses deep learning to complete tasks effectively compared to other AI models. The generative AI landscape covers a range of applications that optimize business processes, create content, brainstorm ideas, write and debug codes, etc., to reduce pressure on employees and complete tasks effectively. Enterprises can use generative AI in various ways to revamp their business model, reduce costs, increase productivity, and generate higher ROI. Generative AI is a subset of machine learning and is different from discriminative AI, which deals with data categorization. Generative AI models help businesses in the following ways: What are Various Techniques Used for Generative AI? Generative AI is not based on any single technique but is a combination of several techniques, such as: These techniques allow generative AI to process input data and generate output as required by the user. This is why generative AI can create versatile types of texts, images, videos, 3D designs, etc. It is highly useful in the medical and healthcare industry as it generates 3D visualizations of DNA structures, proteins, crystals, drug combinations, and so on. However, all of them are not in every generative AI model. AI leaders choose the necessary techniques based on the type of model they want to create and its purpose. Should Start-Ups Explore Generative AI? The answer is yes. Startups, small businesses, and growing companies should explore generative AI to survive in competitive markets. Using the latest technology to streamline internal processes and increase ROI will strengthen the foundation and allow startups to stand alongside established enterprises. Furthermore, startups can directly develop agile and scalable IT infrastructure and save money on replacing legacy systems. However, it’s vital to make informed decisions when bringing major changes to the business model. AI consultants recommend that CEOs understand the following aspects to know how generative AI can benefit their business. 1. Fast Developments in Generative AI Generative AI is evolving at a rapid pace for the last few years. From OpenAI’s ChatGPT to Google’s Med-PaLM, Meta’s LLaMA, Amazon Bedrock, Google Bard, and Microsoft’s integration of ChatGPT 4 with Office 365, the developments are occurring frequently. Entrepreneurs should understand that generative AI and the future are not fixed but constantly evolve. They need to create an infrastructure and work culture where technology and talent can keep up with the developments and adapt to the changes quickly time. Constant investment is necessary to stay up to date. Generative AI is not a one-time investment. 2. It’s More Than a Chatbot Even though we know of generative AI as an advanced chatbot, it is a lot more complex and capable. However, generative AI takes things ahead. It can classify, edit, and summarize almost any type of content. It can answer questions, draft letters, code, outline, strategy, and more. As the models evolve, generative AI can be integrated with enterprise workflows to automate and perform specific tasks. Some AI tools are already providing these services. 3. Scalability and Competitive Advantage Generative AI is versatile and scalable on various levels. Firstly, it is different from other deep learning models that can perform only one specific task. Generative AI can handle multiple types of tasks, resulting in greater efficiency and productivity. This makes it easier to use a single model to perform all the necessary tasks at work and gain a competitive advantage in the market. It can also be scaled to suit the growing business needs. 4. Identifying the Right Use Cases The success of any technology or development can be seen when it is used for the right purpose at the right time and in the right manner. CEOs should ensure that they know why, how, where, and when they want to use the tools in their startups. The budget of the project will also depend on these aspects. For example, generative AI in the customer service department can assist representatives in quickly solving customers’ complaints and speeding up ticket closing. Similarly, the sales and marketing team can brainstorm strategies and use generative AI to create a foolproof promotional campaign and relevant content without spending too much time and resources. CEOs have to identify where to use generative so that they can decide on the next step. 5. Reworking Existing Model vs. Training New Model Is generative AI rewriting your business model? The answer depends on the use cases you finalize and how you want to achieve the results. If you already have accurate ML models, you can customize them and set up integrations with generative AI. For example, using generative AI as a SaaS (software as a service) tool is cost-effective compared to

Purnima Chauhan
June 28, 2023
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AI Development: In-house vs Outsourcing (Complete Guide)

In this data driven world, businesses are turning to advanced tools such as Artificial Intelligence and Machine Learning to extract valuable insights and boost productivity. AI-powered solutions offer great potential for automation, and help in decision-making. However, many companies still need to know-how to implement these strategies properly. As businesses strive to stay competitive in the marketplace, many are turning to the use of AI to gain the competitive edge. But with a wide range of opportunities and methods of development, companies generally opt for outsourcing AI development. In this blog, we will provide a comprehensive overview of the advantages of each approach and the key considerations to take into account while deploying in house vs Outsourced AI development. What is AI Development? AI development refers to the process of creating intelligent machines that can perform tasks without human intervention. It involves a combination of machine learning, natural language processing, robotics and other technologies that allow computers to learn from data and make decisions based on that information. The goal of AI development is to advance automation in various industries, including healthcare, finance, transportation and more. Developers use algorithms and models to create systems that can analyze vast amounts of data quickly and accurately. They also work on improving the ability of machines to understand human speech or written text through NLP technology. As AI technology continues to evolve rapidly, it presents new opportunities for businesses looking for ways to streamline processes or provide better customer service experiences. Also, AI is playing an increasingly important role in business, and its impact is only going to grow. By automating tasks and providing insights that would otherwise be hidden, AI is helping businesses boost efficiency, drive growth, and gain a competitive edge. While some businesses are still hesitant to embrace AI, the benefits are becoming too great to ignore. For businesses that are looking to stay ahead of the curve, investing in AI development is a smart move. Factors to Consider While Choosing In-House vs Outsourcing AI Development There are a number of factors to consider when deciding whether to develop AI in-house or outsource it to a third-party. What is the Difference Between Outsourcing and In-House Development? In-house AI development Are you considering in-house development for your business? As a professional, you know that having your own team with the necessary IT skills and abilities can make all the difference. On the other hand, the management of such a team is a serious load on your budget. While in-house development may be more expensive in the short term, it becomes more cost-effective in the long run. Moreover, for small businesses, an in-house IT department can often handle both the support and development of internal information systems. In-house development also allows for better communication and collaboration between the development team and other departments within the company, leading to more efficient processes and improved project results. By understanding the advantages of in-house development, organizations can make informed decisions as to the best approach for their specific project needs. Advantages of In-house AI development Customization In today’s competitive business environment, having the ability to customize your Artificial Intelligence (AI) solutions is a must. With the ability to tailor the features and settings of your AI solution to meet the exact needs of your business, many companies are opting to develop their own in-house AI solutions. In accordance with the culture Collaborating with a local development team means engaging with individuals who understand the culture, values, and standards of your organization. This type of relationship ensures employees to seamlessly integrate into the organization and add value to their roles. By hiring locally, organizations can benefit from unique perspectives and skillsets that come from having a team that is more familiar with their environment. Outsourcing AI Development Outsourcing AI development can be defined as the process of contracting with an external organization or individual to create, train, and deploy AI models on behalf of another company. There are many reasons why companies might choose to outsource AI development, including lack of internal expertise, time constraints, and cost considerations. When done correctly, outsourcing AI development can be a highly effective way to quickly and efficiently deploy AI capabilities within an organization. By leveraging the expertise of a highly-skilled, external provider, you can streamline your product development while gaining access to specialized engineering & domain expertise. With the right outsourcing partner, you can take advantage of cost savings, faster time to market, and the flexibility to scale your operations as needed. Advantages of Outsourcing AI Development Collaboration with AI Experts When it comes to developing AI products, it becomes crucial to ensure that you have the right experts on board. However, due to the increasing demand for AI, it is difficult to secure full-time experts. Fortunately, outsourcing AI development can help you to bypass this issue. It enables you to access an experienced and professional team without the associated costs of hiring in-house. Cost-Efficient option One of the most obvious advantages of outsourcing is the cost savings that can be realized by making use of the services of Asian countries, where the cost of labor is often much lower than in Western countries. Furthermore, these services are often of good quality, meaning that businesses are able to benefit from low pricing without compromising on the quality of the work produced. Difference Between in House vs Outsourcing AI Development Conclusion When it comes to making a decision about in house vs outsourcing AI development, it is important to consider several factors. Cost is certainly one of the key components, however, it is also important to examine the pros and cons of each model to make the right choice. By understanding the differences between in-house AI development and outsourcing, you can make an informed decision and ensure the best outcome for your project. As artificial Intelligence services become more widely available, businesses are facing the dillema of whether to pursue in-house development or outsourcing for their AI project. While

Yashica Chopra
June 24, 2023
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How AI and Metaverse Have Changed Our View of the World

Metaverse is a virtual world personalized to provide various services to each user. Artificial intelligence is an integral part of Metaverse and can determine the extent of its role in our lives. We’ll discuss how AI and Metaverse have changed our future. Metaverse is the buzzword in today’s market. It is a combination of various advanced technologies like AR, VR, AI, etc. Metaverse allows users to engage with 3D objects in a virtual space. AI and Metaverse are set to create a new reality for mankind. Statistics show that the Metaverse market is likely to reach $783.30 billion by 2030. Many leading multinational giants, like Facebook, Google, etc., are working on Metaverse. But what exactly is Metaverse? What is the role of AI in developing Metaverse, and how will it impact the world? Let’s find out. But before we delve into Metaverse, let’s start with the basics and understand what artificial intelligence is. What is Artificial Intelligence? Artificial intelligence (AI) refers to the simulation of human intelligence in machines that are programmed to think like humans and mimic their actions. AI enables machines to mimic the human mind for decision-making. Artificial intelligence helps computers process vast amounts of information to identify hidden patterns, detect trends, and process information similar to a human brain. AI is categorized into the following: Deep learning and machine learning are subsets of AI and are used in several applications. Artificial intelligence has been adopted by various businesses in recent years. A survey report shows that more than 86% of CEOs consider AI the mainstream technology in their organizations. Close to 85% of enterprises have increased their budget for AI compared to 2019. The global AI market was valued at $93.5 billion in 2021. It is likely to grow at a CAGR (compound annual growth rate) of 38.1% from 2022 to 2030. AI is used by small, medium, and large enterprises from various industries. From Healthcare to manufacturing, every business needs AI to streamline its process. Artificial intelligence is used in the following ways: What is Metaverse? Metaverse is a blend of multiple technologies. It is not a single entity and requires a range of technologies to work together. Metaverse is a collected virtual space that merges the virtual and real worlds. In fact, meta refers to ‘virtual’, and verse is short for ‘universe’. So, Metaverse is a virtual universe. Virtual reality, augmented reality, artificial intelligence, mixed reality, etc., are used to create Metaverse. The virtual worlds can be accessed from computers, smartphones, consoles, VR devices, and more. Metaverse can allow people to interact with the virtual world without moving in the real world. However, it’s important to note that Metaverse is still in the developing stages. Top companies are investing in bringing Metaverse closer to common people. Some smaller organizations are updating their IT infrastructure to be ready for Metaverse by creating virtual worlds that closely resemble real life. That said, a few VR-based apps are also being termed Metaverse by businesses (especially in the gaming industry). These are hybrid models at best and not Metaverse. Role of AI in Metaverse With so many technologies required to develop Metaverse, what role does AI have in it? How important is AI to create Metaverse? The role of artificial intelligence is to support the extensive features of Metaverse. AI will enhance user experience. It will make user interaction with Metaverse a seamless and worthy experience. In short, AI will aid creation, collaboration, interaction, and personalization in Metaverse. It can make the virtual world a delightful experience for users. The Risk of Using AI in Metaverse While AI is great for personalization, it isn’t without risks for users. Micro-targeting can go either way if it becomes manipulative or is missed by people in power. It can be hard to separate fact from fiction if one is not alert. Data manipulation is another risk, which can be controlled through in-built safety/ regulatory algorithms. One way to minimize this risk is by setting up strict regulations about data collection and the role of AI agents in Metaverse. If we can control the misuse of technology, there’s no denying the plethora of advantages it offers to the public. How AI and Metaverse have changed the Future Metaverse will use AI algorithms the way social media platforms use AI for newsfeed personalization, ad targeting, etc. NLP (natural language processing), facial recognition, voice recognition, and other actions are also executed by AI. A Harvard University report shows how AI will affect eight areas of human activities by 2030. The areas include: The report highlights the need for reliable hardware to handle the developments and create a safe space for the world at large to use Metaverse in daily life. Sentiment analysis, emotional recognition, and biometrics (physical + behavioral) will play a vital role in the personalization of the virtual world for a user. Mark Zuckerberg, CEO of Meta, says that it could another five or ten years to make Metaverse a mainstream technology. Right now, it is limited to interactive headsets, AR/VR games, and mixed-reality applications. Conclusion Metaverse will open up new possibilities in technologies and blur the lines between real and virtual. You can create a virtual avatar of yourself to interact with others in the 3D virtual world. It erases boundaries and provides opportunities for businesses to market their products to the right audiences. Metaverse also enhances learning and can provide a user-centric experience. Artificial intelligence plays a crucial role in making this happen by bringing together other technologies to make Metaverse engaging.

Yashica Chopra
May 19, 2023
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The Power of AI in Biotechnology: Revolutionizing Innovation

Artificial intelligence in biotechnology can speed up drug discovery, deliver analytics, accurately diagnose medical conditions, edit gene structures, develop personalized medicine, and do much more to help mankind. Here, we’ll discuss the role and importance of AI in biotech industries. The role of AI in biotechnology is gaining momentum in recent times. The biotech industry is redefining its processes using AL and ML technology to get better, faster, and more accurate results. Be it the pharma industry, healthcare, animal husbandry, or agriculture, AI and biotech are setting the stage for greater advancements and innovations. Biotech or biotechnology is the use of technology in biology. Pharmaceutical companies are the major players in this industry, though others are catching up quickly. Statistics show that the pharma industry will spend around $3 billion on AI in drug discovery by 2025. 82% of industry experts opine that the industry will continue with the digitalization of its operations during post Covid-19 pandemic. The power of big data and data analytics can revolutionize the biotech industry on various fronts. From using machine learning algorithms to natural language processing (NLP), neural networks, and advanced robotics, AI pushes the boundaries and creates more possibilities to improve the quality of life. New biotech companies are entering the global market, using artificial intelligence as an integral part of their business. Reports show that the biotech industry received $2.4 billion in venture funding by December 2022. Many rely on AI Biotech companies and solution providers to integrate the systems with advanced technology and use AI in all verticals. In this blog, we’ll read about the role of AI in biotechnology and how applied AI is helping biotech companies to drive innovation and be ready for future developments. Can AI and Biotech Save Lives? Technically, yes, artificial intelligence and biotech can save lives. This is done by helping researchers create better quality drugs (with fewer or no side effects), correctly diagnose complex ailments in the healthcare industry, identify and change gene patterns to prevent life-altering diseases, etc. Most importantly, combining AI and biotech allows different players in the industry to share information and work together irrespective of geographical restrictions. They can create AI-based pharma (medical) tools and find solutions to save lives. How is Artificial Intelligence Transforming the Biotechnology Industry? The advancement in the biotech industry now relies on big data, AI, and ML technologies. Many experts and top-level executives of leading biotech and pharma companies have said that 2023 is when AI in biotechnology will bring revolution and value and also fit for the purpose it is being used for. AI’s role in biotechnology is not limited to automating repetitive tasks or structuring data flow. Artificial intelligence can help in research, day-to-day work, data analytics, drug manufacturing, and much more. It speeds up the entire process by assisting human researchers to process large datasets accurately in a short time. Diagnosing and Treating Mental Illness The growing cases of mental illness have been a cause of concern in the last few years. Mental illness affects around 13% of the world’s population. The Covid-19 pandemic has led to an alarming increase in depression and anxiety. People with depressive symptoms went from 193 million to 246 million (28% increase), while anxiety disorders showed a 25% increase (298 million to 374 million). Artificial intelligence can help doctors and scientists detect early signs of mental illness and use preventive medication or treatment to help patients feel better. Treating mental illness is hard because the symptoms exhibited by patients are varied and not universally applicable. However, advanced AI programs can observe the brain waves of patients to recommend the best antidepressant therapies for each patient. AI algorithms are being used to study and identify the behavioral loops in addicts to determine the chances of relapse so that physicians can take the necessary action. Furthermore, AI can help create personalized medicine that will be more effective in treating the patient. However, there is a lot more research to be done in this field to help people deal with mental illness and lead better lives. Creating 3D Protein Structures Proteins are one of the four most important macromolecules essential to building life. The scientific community has been using X-ray crystallography and nuclear magnetic resonance to identify protein structures. They have added 187,000 identified structures to the database. However, the process is slow and laborious. Many more proteins are yet to be identified. A UK-based team of AI researchers created AlphaFold, a machine-learning platform that uses the existing database to predict protein structures and build 3D models. The tool takes only a small fraction of the time takes originally to complete the job, that too with greater accuracy. This can help biotech companies identify more proteins quickly and use the vital ones in developing effective drugs. Diseases like cystic fibrosis and muscular dystrophy can be treated with the help of this technology. Gene Coding Identification Machine learning in Biotech can be researchers build powerful models to study and understand human genomics. The next-gen technology used by biotech companies helps sequence a gene in less time and creates an alternative method to homology-based sequence analysis. CRISPR (clustered regularly interspaced short palindromic repeats) can electively modify and edit the DNA or genes of living organisms. This allows scientists to identify and destroy the DNS from bacteriophages that cause infections and diseases. The technology can also help create personalized medicine based on the genome of the patient. This can be a game-changer in treating hereditary diseases and identifying the probability of a patient inheriting a family disease or illness. Lab Assistants AI in biotech is also being used to simplify tedious tasks. Artificial intelligence programs are acting as lab assistants and managing backend work as well as complex tasks like data analytics. H2O.ai is a fast, accurate, and open-source big data analytics platform that allows people to use its statistical models to identify patterns in datasets. Even though the company caters to many industries, many other AI platforms cater exclusively to the biotech, health, and pharma industries. Another role of AI as a lab assistant is the use of robotic devices in research centers, healthcare

Ankush Sharma
April 19, 2023
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Breaking Down Language Barriers: How AI is Revolutionizing Translation

In today’s world, the ability to communicate effectively across multiple languages has become more important than ever. As businesses continue to expand their global reach, the demand for high-quality translation services has increased significantly. Fortunately, advancements in artificial intelligence (AI) have led to the development of sophisticated translation technologies that are transforming how we communicate across different languages. Here, we will explore how AI is revolutionizing translation, the benefits of using the latest AI powered translation technologies, and the potential impact on the future of communication. The Evolution of Translation Technology Translation technology has come a long way. Initially, translation was done manually, with human translators spending hours poring over texts and dictionaries to translate them from one language to another. However, this method was slow and expensive and often resulted in inaccuracies due to the human element involved. With the advent of computers, machine translation was introduced in the 1950s. Machine translation uses software to translate text automatically without human intervention. However, the quality of the translations produced by machine translation was often poor due to the limitations of the software at the time. In recent years, advancements in Artificial Intelligence and machine learning have led to the development of sophisticated translation technologies that are capable of producing high-quality translations in real-time. These technologies are changing how we communicate across different languages, making it easier than ever to break down language barriers. How AI Translates Languages AI powered translation tools use machine learning algorithms to analyze vast amounts of language data and learn how to translate different languages accurately. These tools can process natural language and identify patterns and relationships between different words and phrases. By doing so, they can translate text from one language to another with impressive accuracy. Types of AI Powered Translation Tools There are several types of AI powered translation tools, each with strengths and weaknesses. Some of the most common types include: Rule-Based Machine Translation Rule-based machine translation involves translating text based on a set of predefined rules. These rules are created by human linguists and programmers, and the translation process involves matching words and phrases in the source language to their corresponding words and phrases in the target language. Statistical Machine Translation Statistical machine translation involves analyzing vast amounts of language data to identify patterns and relationships between different words and phrases. By doing so, statistical machine translation tools can translate text from one language to another with high levels of accuracy. Neural Machine Translation Neural machine translation involves using deep learning algorithms to process natural language and translate text from one language to another. These algorithms can learn from vast amounts of language data, making them highly accurate and efficient. The Benefits of AI-Powered Translation AI powered translation offers several benefits over traditional translation services, including: Cost-Effectiveness AI powered translation tools are often more cost-effective than human translators, making them an excellent option for individuals and businesses on a budget. Efficiency AI powered translation tools can translate vast amounts of text quickly, making them an excellent option for individuals and businesses that need to translate large volumes of text regularly. Accuracy AI powered translation tools can translate text with impressive accuracy, making them an excellent option for individuals and businesses that require high levels of accuracy in their translations. Implications for Businesses and Individuals The rise of AI powered translation has significant implications for businesses and individuals alike. For businesses, AI translation tools offer a cost-effective and efficient way to communicate with customers, employees, and partners in different countries and linguistic regions. This can help to expand the reach of businesses and increase their global competitiveness. For individuals, AI translation tools can make it easier to navigate daily life in a new country, communicate with locals, and access information in a different language. Challenges and Limitations of AI Translation While AI powered translation tools offer many benefits, there are also several challenges and limitations to consider. First and foremost, these tools may struggle with idiomatic expressions, cultural nuances, and other subtleties of language that human translators are more adept at handling. Additionally, AI translation tools may not be suitable for translating highly technical or specialized content, as they may not have the required expertise or knowledge. Finally, there is a risk that reliance on AI translation tools could lead to a loss of human language skills and cultural knowledge over time. The Future of Communication The potential impact of AI powered translation technologies on the future of communication is enormous. As these technologies continue to improve, they will make it easier than ever for people to communicate across different languages, breaking down language barriers and promoting cultural exchange. In the future, we may see AI powered translation technologies integrated into everyday devices like smartphones and laptops. This would make it possible for people to communicate with each other in real time, regardless of the language they speak. The impact of AI powered translation on businesses is also significant. As businesses continue to expand globally, the ability to communicate effectively with customers in different languages will become increasingly important. By using AI powered translation technologies, businesses can communicate with their customers in real-time, regardless of the language they speak. Conclusion In conclusion, advancements in artificial intelligence have revolutionized translation technology, making it easier to communicate effectively across multiple languages. AI powered translation tools use machine learning algorithms to analyze language data and identify patterns, resulting in accurate translations. There are several types of AI powered translation tools, each with strengths and weaknesses. They offer cost-effectiveness, efficiency, and accuracy over traditional translation services. As AI powered translation technology continues to improve, it has the potential to break down language barriers and promote cultural exchange, making it easier for people to communicate across different languages in real time. This technology also has significant implications for businesses looking to expand globally and communicate with customers in different languages. Originally Published on The Tech Trend

Shashank Dharasurkar
March 07, 2023
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Unlocking the Future: 9 Mind-Blowing AI Trends to Look Out For

Hey Alexa, “What are the top Artificial Intelligence trends this year? If you ask Alexa or Siri, you will probably hear that the most trending topics are Language modeling, Conversational AI, Computer Vision in Business, and the list. But have you noticed that your assistant is also an example of Language Modeling and Conversational AI? Yes! You are using this advanced technology in your daily life every day without even being aware of it. With the speed at which AI is disrupting industries and even our daily lives, it’s no wonder that experts are calling AI the future of technology. Let’s find out more about current AI trends and how they are affecting the world. Where Is Artificial Intelligence Used Today? Artificial Intelligence is changing the shape of the technology field. It’s now available in various sectors like transportation, manufacturing, health, and finance to automate all the possible systems to increase efficiency and performance. For instance, you can use mobile phones to diagnose diseases. The architecture provides a high-performance system with accuracy and efficiency. Another great example of AI is transportation. A system like Google Maps can analyze the traffic movement speed with accuracy. This program provides records at any time and on-the-spot road incidents. The analysis result includes construction work, heavy traffic, and even accidents. In the manufacturing industry, system maintenance with predictive and preventive mechanisms helps the management teams to avoid downtime. Also, AI systems in quality control help increase work production. The finance sector also leverages ML capability for fraud detection. AI and ML also play a vital role in the smart payment process, insurance, and investment recommendation. PrepAI is another example where AI is getting used in the education sector. PrepAI was originally developed and maintained by the DataToBiz company, which also uses the AI model for different AI services. On this platform, people like teachers or instructors can use the AI model to create various types of exam test papers. How Will Artificial Intelligence Change The World? From smartphones to chatbots, we are already using AI in our daily life. AI is evolving day by day. It observes our routine including our likes or dislikes and our purchases. Then AI specialists, or we can say AI developers, research all that data to train machines on how to learn from it and predict what we want. Following are some predictions done by the USC researchers based on their analysis. Healthcare The research analysis suggests that AI programs with computer vision will allow doctors and well-equipped hospitals to analyze data. Based on that analysis, doctors can customize health care according to individual patient’s genes. AI will be able to diagnose major diseases like brain tumors and will suggest which cancer treatment will be suitable before it worsens. Several types of research are underway to develop AI-powered applications. Those applications are aimed to help doctors diagnose and treat patients with better medical care. You can expect a different future in healthcare as it will adopt robots to interact with the patient. They will check the patient’s health condition and assess the need for a doctor’s appointment. AI will make our life simple with our clinical and healthcare history. Retail According to research, the adoption of ai-powered business intelligence in the decision-making process will make a huge impact on business growth and performance. In the future, AI-powered drones will deliver packages up to 5 pounds in less than 30 minutes. Amazon has already started working on this project with proper safety and reliability measurements for package delivery. There is no fixed date for this delivery to get on the road, but you can expect the autonomous delivery of goods with drones in the next decade. Apart from autonomous delivery, future retail with AI will get individualized with virtual racks. The racks will get customized according to previous history and purchases made by customer choice. Entertainment In the future, users will be able to order a movie that will be completely customized according to their desire. Even working independently, AI will assist humans in their own creative patterns like helping writers to avoid writer’s block by providing suggestions. Furthermore, in the present era, Artificial intelligence is still in action in the form of Google Assistant, Siri, and Cortana. They are able to handle most home devices connected to the internet over voice commands. How Big Is The Artificial Intelligence Market? The growth of AI in every possible application and its easy development dragged government interest toward it. Now the government is also taking a step ahead to invest in AI and its all related technologies. According to Verified Market Research, the global market size of artificial intelligence was worth US$51.08 Billion back in 2020. It is projected to reach up to US$641.30 billion by the year 2028 with growth at a CAGR (Compound Annual Growth Rate) of 36.1% from 2021 to 2028. Apart from that, many sectors like aerospace, healthcare, and manufacturing are adopting AI. Thanks to its in-depth learning and Artificial Neural Network (ANN) mechanism. Also, the capability of big data interpretation and analysis boosted the demand for AI industry solutions. The advanced AI development companies in cloud computing infrastructure and improved dynamic AI solutions have made the potential growth of the AI market. AI is getting used mostly to automate dangerous tasks in the manufacturing industry. Modern AI companies need people with certain skills to adopt, manage, and train AI systems. Top Artificial Intelligence Trends 1. DALL-E Earlier this year, Silicon Valley-based research lab OpenAI unveiled DALL-E, which surprised the internet. In terms of artificial intelligence, this tool is getting considered one of the most advanced systems on the market for creating images. The system works as you can create hyperrealistic photographs or artwork by typing a description. DALL-E is currently unavailable to the public. Researchers, academics, journalists, and artist testers are the only ones who can access to use this system. The company has recently announced that it will invite more people to the event. As

Yashica Chopra
February 13, 2023
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AI Consulting Explained: A Comprehensive Guide for Businesses

AI adoption is increasing in the global market, but businesses still have a few doubts about it. Here, we’ll discuss the need to partner with AI consulting companies and how they can help an enterprise achieve its goals. There have been many technological developments during the last few years in the international market. Businesses are shifting from traditional to modern data-driven models and using cloud services for IT infrastructure. Artificial intelligence has become a common keyword in digitally and technologically transforming business processes. The global AI market is likely to grow at a CAGR (Compound Annual Growth Rate) of 39.7% and touch $309.6 billion by 2026. ‘Many large enterprises are rapidly transforming their systems to adopt AI tools to increase productivity and profits. Small and medium enterprises are a little behind due to cost issues. Many large companies as well as startups are investing in AI and ML models and increasing their budgets to digitally transform their systems. However, startups are realizing the importance of investing in artificial intelligence applications. Several organizations are increasing their budgets to spend more money on AI and ML models. That said, there are a few barriers to AI adoption slowing that slows down the adoption rate. The main barriers to AI adoption are the lack of access to expertise and the cost of developing an AI application from scratch and that’s where AI consulting companies come to play. These roadblocks can be easily overcome by partnering with AI consulting companies. These companies have the necessary talent and tools to provide AI-based services for cost-effective prices. According to MarketWatch’s latest study, the AI consulting services market will earn a multi-million dollar revenue and grow exponentially in the next seven years. Today, many big as well as small. More and more organizations are relying on artificial intelligence consultants for digital transformation services. In this guide to AI consulting, we’ll read more about the types of services offered, how to choose the best AI consultants for your business, and the five best AI consulting solution providers in the market. What is AI Consulting? Artificial intelligence consulting is where AI engineers and experts assist business organizations from various industries to adopt AI applications to achieve their goals. This is easier said than done as it involves a series of activities and is a long-term process. AI consulting companies have several roles and responsibilities, such as: AI Consulting Process Let’s look at the steps that AI consulting companies follow to help businesses leverage artificial intelligence technology in the right manner. 1. Strategy Formation The first step is to create a strategy or plan of action to adopt AI within an enterprise. Here, the AI consultants will have in-depth meetings with the clients to identify areas best suited for AI integration. These are then prioritized to list the required tools for the adoption process. The focus is on strategizing the right path to create the necessary IT infrastructure and data pipelines to integrate AI tools with existing legacy systems. The availability of resources, cost of investment, duration of the project, etc., are considered when planning the strategy. 2. Evaluating Processes and Possible Outcomes Many AI projects fail to take off or end up incomplete due to a lack of evaluation. Whether a business wants to build an AI application from scratch or customize an existing one, the AI consultants will first determine the feasibility of the process and evaluate the possible outcome. These AI experts will assist organizations in choosing projects with commercial viability and success. This reduces the risk of failure and loss of investment. 3. Implementation and Deployment Now, the major responsibility lies with the AI consulting company to implement and deploy the project (building, integrating, customizing, etc.) as per the approved plan. For example, if a business wants to deploy chatbots to assist customer care executives, the AI consulting team will create the necessary framework to set up AI chatbots and automate their roles at the helpdesk. 4. Training and Maintenance Some AI consulting companies also offer training services. After all, the end user/ employees must know how to work with the application. Training sessions are conducted to educate employees about the various features of the new AI application and ways to deal with errors. Alongside this, the consulting company can continue to provide maintenance services if the organization wants. This ensures that AI experts regularly check the systems for errors and upgrade the features to make sure it offers the latest and expected services. 5. Governance and Compliance The AI consulting company is also responsible to ensure that the artificial intelligence systems developed/ customized for the organization are compliant and meet global guidelines. Ensuring data security and developing data governance systems or protocols are a part of the process. The AI consultants may have to add multiple security layers in enterprises that work with highly confidential data. Types of Artificial Intelligence Consulting Firms AI consulting firms are broadly divided into the following types: 1. Tech Consulting These consulting companies are focused on offering tech (IT) based services. They have expert teams to provide off-shore, nearshore, and IT staff augmentation services. 2. Executive Consulting This is also known as top management consulting. These AI strategy consulting companies help businesses understand how and when to implement AI in the enterprise. Large consulting companies also acquire smaller firms and deal with cross-industry adoption of artificial intelligence. 3. Cloud Consulting These AI consulting companies offer cloud-based services. Amazon, Microsoft, and Google are examples of this type of AI consulting. They deal with cloud storage, network management, and cloud computing applications or services. 4. The Top Four Deloitte, EY, PwC, and KPMG are the big four AI consulting companies that have been in the industry for more than 50 years. They offer services to clients from around the world and have premium prices. This makes them cost-intensive for small and medium-sized businesses. 5. End-to-End Consulting Companies like DataToBiz offer end-to-end AI consulting solutions, where they take care of all AI-based processes, from strategy formation to maintenance. The consulting companies may

Yashica Chopra
November 04, 2022
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6 Business Benefits of Outsourcing Your AI Projects

The biggest dilemma for a business is to choose between building an in-house team and outsourcing the AI project to an offshore expert. We’ll discuss the benefits of outsourcing in detail to understand why it is the preferred choice for most enterprises. Artificial intelligence has been a game-changer for many small, medium, and large enterprises. It has made digital transformation possible by helping businesses use data to derive actionable insights and make better decisions. AI can be used in different verticals in the organization. For example, AI applications help the sales team with demand forecasting and market trend predictions. Artificial intelligence is used by the human resource department for recruitment and tracking employee performance. AI has a role in supply chain management, finance, transportation, and customer service. According to Gartner, organizations using AI for customer service are expected to see a 25% growth in customer satisfaction by 2023. More than 90% of the leading business organizations are investing in AI. In fact, 86% of the CEOs considered AI the mainstream technology in their offices as of 2021. This raises the question of whether you need to hire an in-house team for AI projects or outsource the responsibilities to offshore AI developers in India. Outsourcing has its benefits and is a preferred choice for many businesses. Small and medium-sized businesses outsource to avoid infrastructure and maintenance costs. Large enterprises outsource to increase employee productivity. Around 70% of the projects are outsourced to reduce the budget. Flexibility is the second next reason for outsourcing. Read on to understand how artificial intelligence can help your business and why outsourcing AI projects is beneficial. Importance of Artificial Intelligence Artificial intelligence is becoming an imperative part of several businesses because of the range of advantages it offers. How you use AI within the business determines the results. Here are a few important areas where AI is prominently used by leading organizations. Automation Automation is the process of using technology to complete repetitive tasks that are otherwise handled by employees. It reduced workload to save time and energy. It reduces the risk of human error and delivers more consistent results in less time. Machine learning algorithms are used for automation in various industries like healthcare, manufacturing, retail, entertainment, etc. Market and Customer Research The sales team has a lot of responsibility. It has to predict the market trends, understand customer behavior, identify the right time for the promotional campaigns, and align everything with the business goals. AI application will simplify their job while empowering them to use the insights to plan marketing strategies more effectively. Logistics Inventory management, warehouse management, and aligning the movement of stock from the warehouse to the stores or transporting it to the distributors require constant coordination with internal and external teams. A small miscommunication at any stage of the supply chain can lead to delays and losses. Artificial intelligence prevents this by predicting delays in advance and sending automated alerts to supervisors. Unlock the Power of Data Data is available in abundance in today’s world. Enterprises can gather data from several external sources. But how you use the data determines the success of your business. You need the right tools to clean, structure, process, and analyze data to get accurate insights. AI streamlines this process and also provides insights in real-time. You can use the latest data from the market to make decisions instead of relying on outdated information. Competitive Advantage Using AI tools will give you an edge over other businesses in the same industry. It helps small and medium-sized businesses establish themselves in the market despite the strong presence of global enterprises. Artificial intelligence is ‘the key’ you need to survive competition, capture markets, and expand your customer base. Disadvantages of In-House AI Team for AI Projects Having learned how AI can help your business, you should decide between building an in-house team and outsourcing the projects to AI consulting companies in the market. It might appear tempting to start from scratch and develop an in-house team so that you will always have someone working on the AI tools. However, you should consider the following aspects before going ahead with a permanent team within the enterprise. Shortage of Skilled Professionals Despite the increasing demand for AI and ML engineers, data scientists, etc., there aren’t enough professionals to bridge the gap between demand and supply. In such instances, hiring talented and experienced professionals in a short time is almost impossible unless you are a leading global organization. Furthermore, there’s no guarantee that the professionals will stay with your business. They can move to another company if they get a better offer. This means you have to start the recruitment process once again. It will lead to more delays and cause a waste of valuable resources. Cost Intensive The cost of having an in-house team doesn’t end with recruitment. You have to pay salaries and provide the necessary infrastructure and resources for the team to work on the AI projects. You also have to deal with the cost inflations due to additional requirements/purchases, pay hikes, and losses if the project is not successful. An in-house team is expensive for a business unless you have the budget to sustain an R&D department and invest millions into it regularly. Machine learning outsourcing will cost less and deliver faster results. Involvement from Different Departments The in-house cannot work in isolation. It needs input from other departments and should have team members for the same. However, not every business has enough manpower to spare employees from one department to work in another. Asking the employee to handle everything will lead to stress and decreased productivity. Access to Quality Data for Training Models Quality data is the key to accurate AI models. The algorithm will deliver results based on the input data you provide. But where does quality data come from? Data available online cannot be directly used to train models. It needs to be cleaned, formatted, structured, and processed before being fed into the model. The in-house team will spend most of the

Shashank Dharasurkar
October 27, 2022
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A Definitive Guide To Machine Learning Consulting

Planning to integrate artificial intelligence and machine learning into your daily business operations? If yes, then what’s the best way to go about it? If you are confused about how to leverage machine learning or artificial intelligence capabilities to scale your business, then you need an expert to guide you. This guide will walk you through the whole process of ML and AI consulting and whether it’s the right choice for you. What is Machine Learning Consulting? The goal of AI/ML consulting is to help businesses improve their performance and productivity by using AI technologies. The main focus of artificial intelligence is to exploit machine learning to increase companies’ value in an environment of rapid change and intense competition. AI consulting companies help their clients design and develop advanced AI-based products and solutions by developing AI-driven algorithms and machine learning tools. In order to ensure maximum results, it is essential to design, implement, and integrate Artificial Intelligence into the business environment of various organizations. The demand for artificial intelligence-driven products and systems is high at present. But, there are still limited options available. The services offered by AI consultants include: What Does A Machine Learning Consulting Firm Do? There are many reasons why companies need consultants, such as a lack of expertise, existing commitments, government regulations, or the need for an unbiased perspective. While consulting firms perform varying roles and responsibilities depending on the industry and the company’s needs, their primary goal is to improve business efficiency and profitability. Consulting firms begin their work with the following tasks. The Process Starts With Knowing What Your Business Needs Every consulting project begins with some business need. Business requirements are still one of the biggest reasons for the failure of consulting and software projects. It can be choosing the right location to install your next branch or selecting the right audience. There is a particular issue with ML consulting, as it is at the intersection of consulting and software development. Setting Up the Team and the Process Machine learning is not necessary for all business problems. Problems that cannot get reduced to a set of rules make sense for machine learning and other approaches. The performance and maintenance of rule-based systems are better than machine learning when the rules are well known. ML can be useful for solving particular problems, but the project team, stakeholders, and high-level targets needed get decided. The Process of Collecting and Exploring Data It is relatively simple to do this if the company already has the data. Else consultant has to collect all the data to understand the business problem. Afterward, consultants must verify that data labels are accurate and do not conflict with each other. If data isn’t readily available, you can also have options like leveraging online data, paying for labeling, or using novel machine learning techniques such as one-shot learning. The Model Development Process. Developing a machine learning model that performs more accurately requires thousands of experiments. It is a trial-and-error process involving the latest research, a thorough understanding of business dynamics, and data analysis skills. For accuracy testing, all models get tested against the same data set. Full-Stack Application Development The model development and integration for production require additional time and resources. In most cases, ML models get embedded into APIs which makes it easy to integrate them into applications. Application development, which implements the ML model and integrates it into decision-making processes, can be more challenging than modeling itself. When developing applications, integrating them into existing enterprise systems is necessary, which requires an external developer’s involvement. To put the model into action, it is necessary to address the scalability and data security issues. Why Does Your Business Need Machine Learning Consulting Services? If you are just getting started with machine learning, it can be difficult to differentiate a top consulting firm from an upstart. You should consider these points before working with a consulting firm. They Are A Time Saver McKinsey estimates that artificial intelligence and machine learning will replace 30% of current jobs by 2030. Machine learning service providers can save you a lot of time. You can find running a machine learning campaign difficult if you don’t have any AI training. The advantage of hiring a highly regarded machine learning company is that they have expertise in all aspects of machine learning and can launch your campaign quickly. Experienced consultants are familiar with best practices. For instance, A lean consultant can quickly pinpoint inefficiencies in a company’s manufacturing process. Business owners do not need to create something from scratch or waste valuable time on tasks an expert contractor can complete. They Are Result Driven A good machine learning firm will always take the time to understand your business, your goals, and your needs before creating a machine learning campaign for you. In this way, they will design and implement a machine-learning strategy that corresponds to your business goals and provides you with the desired outcomes. It Is Financially Profitable It is important to have a lot of data to make good decisions when creating a machine learning campaign. In order to hire a machine learning consultant, you will need access to various programs and software, which can cost quite a bit over time. When you hire a machine learning consultant, you will have access to many different programs and software, which can be expensive over time. Additionally, you pay only for the services that you need, when you need them. An ML consultant with similar expertise can save hundreds of dollars compared to hiring salaried employees. Besides, consultants with expertise in many areas can identify pinpoints where you are currently overspending and suggest ways to cut it. Providing Support For Data Preparation The data preparation and collection are essential for modeling and training ML, as well as the foundation for deep learning and AI. Also, for combining data sets, renormalizing data, and preparing your database for successful implementation, a good ML consultancy can provide you with helpful advice. Consultants

Drishti Patel
October 14, 2022
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6 Reasons To Hire a Machine Learning Developer

Artificial intelligence and Machine Learning are undeniably transforming and integrating themselves into every aspect of our everyday lives, from entertainment and social interactions to the workplace. Artificial intelligence, according to experts, will advance a company into the next generation, revolutionize data management, and improve the whole consumer experience. There are many business applications for AI and machine learning, and as these applications become more widespread and sophisticated, we can only anticipate an expansion of this list. 6 Reasons to Hire a Machine Learning Developer Here are a few of the reasons you should hire a machine learning developer: 1. Supports Real-Time Decision Making Big data’s potential is expanding quickly, thus you must connect users and providers (buyers and sellers) instantly. Businesses must instead use data and analytics to quickly determine the best course of action based on the current situation. Your consumers will appreciate personalized services, which will increase profits. A machine learning developer helps businesses achieve real-time decision-making by drawing insightful conclusions from the data. 2. Enables Automation That Replaces Manual Efforts ML technology advances industrial automation by replacing manual jobs that incorporate unpredictable elements like changeable parameters, external causes, and internal system changes. Industrial automation in the 20th century focused on employing machines to reduce predictable and repetitive human tasks. An ML developer gives businesses the ability to make quick judgments and automate operations by creating predictive data models. One such is Adobe Target‘s Auto Target, a potent AI technology that employs machine learning to create automated tailored experiences. Personalization in Adobe Target is based on a set of experiences chosen by the marketer. 3. Effectively Address Security and Network Challenges Cyberattacks, network breaches, and other security flaws sometimes occur in real-time without warning, giving users little opportunity to take action. One of the biggest cyberattacks in history occurred in 2018 when a series of DDoS strikes targeted GitHub and Arbor Networks in the US. Any network intrusion must be promptly detected and stopped by enterprises in order to avoid service interruptions and data leakage. ML developers are capable of creating algorithms that are capable of tracking network activity to quickly identify anomalies so that preventative steps can be taken. Additionally, as ML algorithms take the place of manual investigation and analysis, they self-learn and adapt to change, which further enhances the condition of cyber-security. 4. Improves Marketing Results The branch of AI known as machine learning focuses on creating intelligent machines that can operate independently of human intervention. Additionally, a machine learning developer helps businesses save time and money in the marketing sector as well. In marketing initiatives, machine learning can be an amazing and potent multiplier. Constant messaging, trends and changes in consumer behavior, targeted marketing techniques, etc. are all made possible by machine learning engineers. Social media websites can be used to develop micro-marketing campaigns. 5. Manages Unstructured Data Large amounts of unstructured data can take a long time to clean up. Any organization that evolves over time gathers a lot of fresh information. For instance, if you are in the air freight forwarding business, you will need to process large amounts of data on services, rates, etc. within a short period of time in order to evaluate it and obtain insights about potential future patterns. Managing and removing massive information indexes is one of machine learning’s most important applications. The information is easier to process, obtain, and retrieve thanks to machine learning. 6. Increasing Customer Satisfaction Currently, machine learning is used to improve customer experience, which results in increased customer loyalty. It is done by looking at the customer’s buying habits. Many organizations all over the world already use this technology. According to research, 76 percent of business owners agreed that their profitability increased as a result of incorporating machine learning into their processes to understand client behavioral patterns. Google and many other large websites are using this technology. You may have observed that when using websites like YouTube, LinkedIn, etc., you frequently receive recommendations for various goods to buy or individuals to connect with. With the aid of machine learning, the ads and friend suggestions are handled. How To Hire A Machine Learning Engineer When hiring a machine learning engineer, who can be a valuable asset for your business, it is advised to exercise extreme caution if the company is investing in the development of artificial intelligence and machine learning. As a result, there are some essential factors to consider when hiring a machine learning engineer or specialist. What to take into consideration when you want to hire a machine learning developer is covered in full below. 1. Technical Skills For these professionals, full-fledged technical skill in coding and programming is essential in order to tackle such assignments. Here, you must check the applicant’s technical specialization and administer the coding test to confirm that she/he is capable of overseeing the creation of AI and ML models. Make sure you have qualified professionals to hire the best applicant so you can evaluate their technical talents. A machine learning developer should have knowledge of languages like python, frameworks like Pytorch or TensorFlow, algorithms like Scikit, and many others. Make sure you test all the necessary technical skills before hiring. 2. Interactive Communication Skills The ability to communicate with others, which is necessary for collaboration with colleagues, should be taken into account when trying to hire a machine learning engineer. Before beginning the project, AI and machine learning professionals should agree on a framework for communication with the company. Therefore, if you are concerned about a candidate’s communication skills, you should assess their capabilities to ensure effective communication. Wrapping Up Finding a suitable AI or machine learning professional would be difficult and time-consuming. To prevent confusion between data analysts, data scientists, and machine learning engineers, it provides basic stages of vacancy description with a precise set of responsibilities. In order to recruit a machine learning engineer that is an expert in his field, one must have a complete understanding of technology and competence. So, to