TOP ARTIFICIAL INTELLIGENCE FUNDING AND INVESTMENTS IN MARCH 2020

| April 2, 2020

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What Artificial Intelligence has in its baggage is known to everyone and thus realizing its potential its funding projections are expected to rise to $46 billion spending by 2020. Billions of dollars are being invested by the venture capital industry to catalyze the rapid technological breakthroughs to enable a future where AI seems plausible. Attaining utmost Superintelligence is still a matter of mystery, but today various industries have employed some of the most innovative forms of artificial intelligence to power our daily tasks. Serving with great benefits AI has endless applications. To encourage those innovations, numerous investors are coming at the forefront to ignite the wave of the advanced fourth industrial revolution. Therefore, we have brought you some of the most recent and significant AI funding and investments of 2020.

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OTHER ARTICLES

How do HD maps support autonomous driving safety?

Article | July 26, 2020

Are self-driving cars safe? As the automotive industry moves towards higher levels of automation, it’s important for the answer to this question to always be yes. At TomTom, it’s our vision to create a safe, connected and autonomous world – and a big role in making autonomous driving safer is played by ADAS and HD maps. Maps – ADAS and HD – are one of the four pillars of autonomous driving. Together with onboard sensors, driving policy and actuators, they form the technology that enables automated and autonomous driving. HD maps specifically improve localization to centimeter-level accuracy and sensor perception, which leads to safer path planning by automated driving systems.

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Why Humans Need Chatbots And Chatbots Need Humans

Article | July 26, 2020

Chatbots have come a long way in the past few years. The improvements in technology have enabled developers to expand on bot capabilities far beyond just functioning as a FAQ. Today, the automation of chatbots can process orders, perform financial transactions, make bookings, and much more. (Check out other intelligent functions here.) However, as intelligent as bots can be, no chatbot can handle and resolve all your customer queries. It simply cannot answer the infinite number of questions a human may throw at it. The technology is simply not there yet, and it may never truly get there. But perhaps more importantly, brands shouldn’t want a bot to manage every customer query. A bot working independently of human involvement won’t always deliver the best results for customer or agent. It’s the combination of chatbots and human agents that takes customer service to new heights. What you need is a smart and efficient way of translating your organization’s unique customer service philosophy into appropriate action so that every question is met with an answer in the best way possible – whether that be by bot, human agent, or a blend of both. To deliver this, you have to pay attention to the who, what, when, and where of customer engagement. You need to know who your highest-value customers are so you can always route them to a human agent, for example. You need to know what they need help with so a simple question can be managed by a bot. And the list goes on. Here’s why humans need chatbots, and chatbots need humans – and how you can achieve this perfect balance to deliver support that will exceed customer expectations and generate substantial ROI. Why humans need chatbots There’s no doubt that supplementing customer-facing roles with automation can yield fantastic results. The launch of McDonald’s self-serve kiosks is a great example of this. By giving customers the option of ordering their meal through a kiosk, or through a cashier, McDonald’s demonstrates the success you can achieve by combining automation with human. Here are just some of the benefits it brought to the customer and employee experience: 1. Automating large portions of simple queries so workers have more time to focus on other, more complex tasks 2. Reducing monotonous, repetitive queries to improve employee experience 3. Catering to customer preferences – choose quick automated service or deeper human engagement 4. Reducing queue times, in turn improving customer experience 5. Lessening the opportunity for human error 6. Generating ROI by reducing staff numbers These results almost identically mirror the benefits that intelligent chatbots can provide customer service teams. By implementing a bot, a large portion of frontline support can be automatically managed by the bot which: 1. Gives agents more time to handle complex questions 2. Reduces the monotony of answering repetitive questions 3. Allows customer to choose between chatting to a bot or an agent 4. Reduces wait time and queue length (through bot’s ability to handle infinite simultaneous conversations), in turn improving customer satisfaction through quicker resolution 5. Eliminates human error in data entry 6. Generates substantial ROI through lower service costs See how closely those benefits match? Recommended reading: Chatbot ROI Calculator Why chatbots need humans The relationship between bots and humans isn’t a one-way street. While agents need bots to provide more effective and efficient support, bots need agents to provide the personal, ‘human’ touch that many situations call for. In our latest 2020 Live Chat Benchmark Report, we found that chatbots handle 68.9% of their chats from start to finish – although an impressive stat, it still shows that many queries require an agent’s touch. Recommended reading – 2020 Live Chat Benchmark Report There are always going to be situations that call for human assistance: canceling a subscription, reporting a lost or stolen credit card, or registering a serious complaint. Or maybe the topic is sensitive, and your customer would feel more comfortable explaining their situation to an agent. Similarly, some (though increasingly less: stat?) people are still wary or reluctant to communicate with bots and prefer to only speak with a live agent. To cater to these customer preferences, it’s vital that these customers can be routed past or transferred from your chatbot to human agent without effort and without having to repeat themselves. It’s important to note however, that transferring from bot to agent isn’t always just in the interest of the customer – it can often benefit the customer service team too. This is because not all queries are equal. For example, if a customer reaches out asking about a bank’s opening times, this can be easily managed by a bot. However, when the same customer asks about a loan, this high-value interaction may dictate that – according to your unique customer service view – a human agent takes over immediately to ensure the customer receives the best experience and you close the deal as quickly and effortlessly as possible. If your chatbot can’t do this, turn it off and find a chatbot that can (we can help with that). How to create the perfect chatbot – human (agent) balance To begin creating the right balance between chatbot and human, you need a bot that’s widely accessible to today’s digital-first consumers; your bot needs to be where they are, wherever they are. Comm100’s AI Chatbot can serve customers on web, in-app, Facebook, Twitter, WeChat, WhatsApp for Business, and SMS. You also don’t need to build separate chatbots for each channel. Simply select the channels you want your bot to be available on (hint: all of them!) and you’re off. Although your customers will know they are speaking to a bot (and you should make this clear to them to set expectations), you need a bot that understands natural human language. Comm100’s AI Chatbot harnesses the world’s most advanced NLP engine so that it can understand your customers’ goals and provide the answers they’re looking for. Better still, add a large range of off-the-shelf integrations to this, and the Comm100 bot can begin performing actions on behalf of your customers – from tracking an order and paying a bill, to booking a flight. By resolving a large portion of your frontline customer service questions, your agents will have more time to focus on higher-value queries and customers that matter most to your bottom line. Recommending reading: Comm100 Chatbot Resolves 91% of Assigned Live Chats for Tangerine As we’ve discussed earlier, there will be times when you or a customer would rather connect with an agent than a bot. It’s crucial that your bot offers this flexibility. Firstly, your bot should be able to give the customer the option to speak to an agent at any time. Eighty-six percent of consumers believe they should always have the option to transfer to a live agent when dealing with a chatbot. You can easily set this option up within the Comm100 AI Chatbot. Next, you need a bot that can automatically identify the conversations that you want an agent to manage. This requires training your bot on the topics – ‘intents’, in bot lingo – that your customers will bring up. If there are specific intents that are of high value to you, you can tag them so when a customer mentions it, the bot recognizes it and automatically transfers the chat to the appropriate agent or department. The bot can also be trained to notify an agent or escalate the conversation when asked a question it can’t answer or if a visitor is clearly frustrated. As a failsafe, your agents should also be able to monitor bot conversations and take them over in these situations. Wrap-up Chatbots will never replace whole customer service teams, and nor should they. The ‘human touch’ is still essential to customer support, and we are a long way off until this changes. However, if implemented intelligently, bots can resolve a great portion of customer queries without any human involvement, allowing team sizes to reduce, or remain the same in the face of increased support volume. Take Tangerine, an Australian telecom company, for example. They experienced rapid growth, which in turn produced a surge in chat requests. By implementing Comm100’s AI Chatbot, up to 91% of assigned live chats were resolved by the bot without any agent involvement. As a result, Tangerine could manage the increase in chat volume without hiring and training more agents. And when high-value customers reached out, their agents were free to provide them with the best experience.

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Effects of Artificial Intelligence on Software Development

Article | July 26, 2020

What’s the core of those drone-supported Amazon deliveries, online food orders, the ability to watch your favorite shows on Netflix, and virtually augmented monitoring of your upcoming trip to Disneyland? Software! They constitute a significant part of almost every evolution we see around us. But how are the developers managing to yield so much from computer programming? How are they able to enrich so many lives through their creations all over the world? The answer is simple — Artificial intelligence (AI). Undoubtedly, AI is one of the leading technologies now, and it has the power to transform every bit of any business’ functionality. The software industry is not behind in making the most of AI and delivering intelligent and intelligent software. On the contrary, modern enterprises are convinced to adopt an entirely new software development paradigm to stand out from the competition. Traditionally, machine learning was predominant in the Software Development Lifecycle (SLDC). Even though it could encode numerous tasks in a computer program, it took relatively more time to be finalized. It required developers to put the exact requirements together first and hand them over to engineers. And then, engineers programmed the code accordingly. However, AI came with its advantages. As a result, it is reshaping the modern world of automated testing, Agile test software, and ultimately the entire software development. So if you see bots accompanying computer programs to make software development even easier, faster, and smarter in the future, it will be because of AI. So if you are already thinking of potential changes AI will bring to your software development process and how you can reap all the benefits of AI software development, stay tuned! Area of AI Software Development Artificial intelligence has a significant impact on various aspects of software development, for example, software testing, coding, designs, etc. Let’s now discuss what role AI will play in the current and future of software technologies by reshaping the major software development areas. Software Design Process will Improve Designing software is one of the most complicated and error-prone stages of software development. Therefore, specialized skills and the right experience are crucial for designing and planning software development projects to come up with an absolute solution. Moreover, the software designs are mostly subjected to dynamic changes as clients may suggest changes in different stages of software development. AI-powered systems such as AIDA (Artificial Intelligence Design Assistant) can eliminate such complexities in the design process. Time & Money Saving Software Testing Traditionally, software testing takes a lot of time, especially when there are changes in the source code. Plus, it's costly, too! But in the end, it’s one of the essential software development stages as it ensures product quality. Therefore, there’s no room for error. Thankfully, there’s AI and a variety of software testing tools. Testers can utilize them to develop test cases and carry out regression testing. This kind of automated testing is relatively faster, smarter, and astonishingly time and money-saving. On top of all, it's error-free! Easy Data Gathering and Analysis Data gathering and data analysis are the most fundamental stage of any software development lifecycle and need a significant amount of human intervention. The project team has to come up with all the information necessary for the software development, and clients' input can be dynamic. Automated data gathering through various AI tools such as Google ML Kit can be the best option to ease the process. It can take care of specific data-gathering processes without the need for significant human intervention. Say Bye to Manual Code Generation Generating huge codes requires a lot of labor, time, and money. Therefore, simplifying the code generation process is significant because code writing is crucial for any software development life cycle. While traditional code generation can fall short in identifying the target goals effectively, automated code generation can be a game-changer. This is because AI tools typically generate snippets of reusable codes and write code lines as instructed. As a result, they save a substantial amount of money, labor, and time. Benefits of Artificial Intelligence in Software Development Incorporating artificial intelligence in software development can do wonders. Considering the incredible impact of AI on software development and the possibility of incredible transformations in the future software technologies due to AI, here are some promising benefits of AI software development. Enhanced accuracy in estimates Conceptual decision making Error-free end product Easy bugs and error detection Improved data security Conclusion The software development landscape is rapidly changing, and AI has a lot to do with it. Being an enterprise, you need to understand the benefits of AI and how it is enriching human lives worldwide. It's hard to deny the tremendous pressure on the current software development industry from the demand for applications. However, it’s one of the fastest-growing industries, and AI can simplify it with secure, unique, and scalable solutions. Unquestionably, AI software development is the future, and adopting it is the best decision enterprises can make. Frequently Asked Questions What are the things to consider when adopting AI for software development? It would help if you consider the following factors to reach new heights with AI software development: Cloud is necessary for AI AI solutions are much more than implementing machine learning algorithm AI is near real-time or real-time Big data is required for AI Machine learning-powered AI solitons may need frequent retraining What are the real-world examples of integrating AI into software development? Here are some examples of AI tools that several organizations are using for efficient AI software development: Deep Code Stack Overflow AutoComplete Google Bugspot Tool w3C What are the top machine learning and AI tools software developers should consider? Generally, Machine learning software, Deep Learning software, AI platforms, and Chatbots are the four major types of software. Apart from the tools mentioned above, developers should consider the following AI tools for the enhancement of software development: Google Cloud’s AutoML Engine Kite AIDA Testim.io IBM Watson Amazon Alexa Cortana TensorFlow Azure Machine Learning Studio { "@context": "https://schema.org", "@type": "FAQPage", "mainEntity": [{ "@type": "Question", "name": "What are the things to consider when adopting AI for software development?", "acceptedAnswer": { "@type": "Answer", "text": "It would help if you consider the following factors to reach new heights with AI software development: Cloud is necessary for AI AI solutions are much more than implementing machine learning algorithm AI is near real-time or real-time Big data is required for AI Machine learning-powered AI solitons may need frequent retraining" } },{ "@type": "Question", "name": "What are the real-world examples of integrating AI into software development?", "acceptedAnswer": { "@type": "Answer", "text": "Here are some examples of AI tools that several organizations are using for efficient AI software development: Deep Code Stack Overflow AutoComplete Google Bugspot Tool w3C" } },{ "@type": "Question", "name": "What are the top machine learning and AI tools software developers should consider?", "acceptedAnswer": { "@type": "Answer", "text": "Generally, Machine learning software, Deep Learning software, AI platforms, and Chatbots are the four major types of software. Apart from the tools mentioned above, developers should consider the following AI tools for the enhancement of software development: Google Cloud’s AutoML Engine Kite AIDA Testim.io IBM Watson Amazon Alexa Cortana TensorFlow Azure Machine Learning Studio" } }] }

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AI TECH

Artificial Intelligence in a post-covid world: 2021 and beyond

Article | July 26, 2020

COVID-19 has impacted every aspect of our lives including the way we do business. In fact, according to a recent survey by McKinsey, COVID has accelerated companies’ digital transformation journeys. In a post-COVID world, there will be an even-greater acceleration of AI adoption by enterprises. AI business applications will be centered around automating tasks, forecasting supply disruptions, and enhancing customer behavioral analytics. There will be a rise in industry and sector specific AI applications where business domain knowledge and business content data are the main differentiators. However, increases in AI adoption rates do not necessarily translate into higher success rates. To avoid failure, business executives need to develop robust AI strategies and metrics, enhance data quality, and focus on AI integration and governance. Key trends and applications for 2021 and beyond are as follows: AI and Healthcare Artificial intelligence played a crucial role in the detection of COVID-19. Indeed, we have seen the emergence of the use of AI at hospitals to evaluate chest CT scans. With the use of deep learning and image recognition, COVID patients could be diagnosed thus enabling the medical team to follow the necessary protocols. Another important application was the triage of COVID-19. Once a patient has been diagnosed with COVID, AI has been used to predict the likely severity of the illness so the medical staff can prioritize resources and treatments. In a post-COVID world, we will see increased use of AI in detection of illnesses, triage of patients, and drug discovery. According to a recent market research reported by PRnewswire, the market size for global healthcare IT is expected to reach $270 billion by 2020. The increase will be driven by COVID-19, government policies, and the use of technologies such as artificial intelligence and big data. AI and Supply Chains Coronavirus has highlighted the need to re-think traditional supply chain models. There will be an increase in the use of technology such as artificial intelligence, Internet of Things, and 5G to make supply chains more efficient. Artificial intelligence applications will focus on improving end to end visibility, analyzing data to detect anomalies, and forecasting supply and demand outlooks thus making supply chains more resilient. AI and Retail The pandemic has changed what and how consumers buy, with retailers forced to grow their online presence. E-commerce has been put at the forefront: in the first six months of 2020 consumer spending with US retailers increased by about a third compared for the same period in 2019 according to Digitalcommerce360. According to new market research reported by PRnewswire, AI in retail will be worth about $20 billion by 2027. When it comes to retail and ecommerce, we can find AI applications in several areas including customers analytics for product recommendations, targeted marketing, and price optimizations. For the latter, AI is applied to analyze patterns and data on customer profiles, their purchase power, product specification, timing of purchase, and what the competition is offering. The outcome of the analysis will set the pricing strategy. Several companies use AI to set their pricing strategy on a frequent basis, for example Amazon’s average product’s cost changes about every 10 minutes according to Business Insider source. AI and Intelligent autonomous agents COVID has highlighted the need to deploy intelligent autonomous agents that cannot catch diseases to fight against the pandemic. We have seen both robots used at hospitals to diagnose COVID-19 patients and drones deployed to monitor if the public is adhering to social distancing rules. An ABI research showed that mobile robotics applications market size will increase to $23 billion by 2021. This increase is mainly due to applications that disinfect, monitor, and deliver materials. The integration of AI with drone technology and robotics will create new application opportunities and will make them mainstreamed across several sectors. AI and Education Education is another sector that was badly hit by COVID. According to Unicef more than 1 billion children are at risk of falling behind due to school closures. The pandemic has highlighted the need for educators to adopt digital solutions to minimize learning vulnerabilities across the globe. AI application in education will mainly focus on personalized learning where the technology is used to design and tailor training materials that matches the student’s ability and learning preferences. Other applications include the deployment of voice assistants to interact with educational material and the use of AI to support teachers in administrative tasks. AI and Digital Twins The pandemic has accelerated the adoption of digital twin technology. Digital twins are replicas of physical assets such as cities, offices, and factories. This technology became crucial in testing pandemic scenarios and emergency plans. Digital twins technology is expected to reach a global spend level of about $13 billion by 2023 fueled by AI and machine learning according to Juniper Research. When integrated with artificial intelligence and IoT, digital twin technology becomes very powerful when trying to test scenarios and predict bottlenecks, breakdowns, and productivity. AI and Ethics Over the last year, we had several prominent examples of AI ethics issues. The first example relates to facial recognition: after several calls against mass surveillance, racial profiling and bias, and in light of Black Lives Matter movement starting in the United States, several tech companies such as Microsoft banned the police from using its facial recognition technology. The second example relates to the use of an algorithm to predict exam results during COVID-19 period: after accusations and protests that the controversial algorithm was biased against students from poorer backgrounds, the United Kingdom government was forced to ditch the algorithm. In the absence of regulations and tightened frameworks, ethics will continue to be the main concerns surrounding the use of artificial intelligence.

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ctsIT.com is a mid sized services & solutions partner to Technology Firms and Enterprise Customers in North America, Singapore , and India. What we bring to the table is a passion to deliver – every engagement fosters a long term client relationship providing predictable service.

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