The new era of artificial intelligence (AI) has arrived, opening up a world of opportunity for significant progress, but also exposing the growing gender gap in digital literacy. UN Women highlights the major gender biases that have been identified in AI tools. In addition, the majority of tools are designed from a male perspective, further excluding women from usability. Interdisciplinary researchers were given access to the development stages of ChatGPT and its successor, GPT-4, and reported that "the solution may represent various societal biases and worldviews that may not be representative of the user's intent or widely shared values". As an entrepreneur, a woman, a mother, and a woman of color, I am committed to promoting inclusivity and equality in the business world.

As technology advances at an exponential rate, the gaming industry has been one of the early adopters of artificial intelligence (AI) to enhance user experiences. With the global AI market expected to reach $190 billion by 2025, and the global video game market expected to reach over $268 million by 2025, the combination of both of these has the potential to revolutionize e-gaming. With the ability to create more immersive and personalized gaming experiences, AI has already begun to positively affect the gaming sector by providing gamers with smarter and more realistic opponents, advanced game mechanics, and an immersive gaming environment. With AI-powered gaming platforms, gamers can expect a more sophisticated and dynamic gaming experience. AI-powered games can adapt to players' skills and provide customized challenges that are tailored to their abilities.

AI-based Chatbots are used everywhere, including as lead-generation tools on websites, personal shoppers in eCommerce, and even healthcare assistants in the medical field. It's no wonder that chatbot development is a big priority for many companies. In this article, we'll show you how to build a chat bot (based on experience from Topflight Apps). Chatbots have several benefits, including making customers happy by quickly answering their questions, hosting multiple conversations at once, and offering better user experiences. Unlike human employees, chatbots never have a bad day, go on vacation or get tired.

Deep learning is set to transform entire industries and create new opportunities on a scale not seen since the Industrial Revolution in the 19th century. But while recent years have seen breakthrough innovation in deep learning, developers still face formidable obstacles in creating effective deep learning models, particularly when aiming to put them into production. Amid major advances in the field of deep learning, thousands of companies and startups are building products and services that rely on this technology. Building the deep neural models needed to power business applications requires not only deep expertise in the field, but also substantial time and resources devoted to critical tasks like model design, training, quality testing, deployment, maintenance and periodic updates, and revisions. Given that deep learning's value proposition promises to unlock new efficiencies, the expensive and cumbersome process of actually creating and deploying deep learning models has been a sticking point for many organizations seeking to leverage the technology.

Almost every enterprise believes data to be one of their most important assets, but most would admit they are not leveraging their data to its full potential. That's because making data easily accessible to employees is surprisingly hard work. It requires a concerted, ongoing effort to gather, structure, and tag data in order to turn it into knowledge, capable of being found in the moments when it can be most useful, using a voice AI knowledge assistant. Of course, this has always been true regardless of the state of technology, from ancient libraries indexing vast physical volumes to today's cloud-based search engines crawling millions of gigabytes of data. We can take for granted the magic of the now-ubiquitous digital keyword search, which has delivered us the power to have any data point just a few mouse and keyboard clicks away.

Subject matter experts are hard to come by when looking to hire in specialized areas. However, many companies do not realize that the specialties they are seeking already exist in their organization – using data connection. With proper data connection powered by artificial intelligence and machine learning, subject matter experts can be identified internally, which helps to – reduce costs and get the most out of your existing workforce. In addition, data connection and a holistic approach to knowledge management give other employees the ability to know what the experts know with just a few clicks. Valuable data sits all around your company in different data sources.

When a large IT company begins looking for smaller mid-market firms to buy (under $30M in transaction value), five key factors usually influence their decision. These factors are crucial as the larger company works to maintain its market advantage and grow its business. If you are a small, emerging growth IT company and can answer "yes" to the following questions, then you may be a desirable acquisition target for a larger firm. The questions may seem obvious – perhaps easy. But effective, compelling answers are not.

The future of work is a hot topic among businesses now and has been since the shift to hybrid work. While processes and personnel undergo significant transformations, business and IT leaders must focus intensely on the digital employee experience (DEX) when analyzing and deploying any operational change to the status quo of their current processes. The digital employee experience (DEX) interprets how digital workplace strategies impact employees' overall day-to-day experience. An enterprise's workforce is the bedrock of resilient and sustainable operational shifts. Measurable success cannot be achieved without employees on the same page.

Say the words "synthetic media," and most people will immediately think of deepfakes. With the rise in stories about issues with deepfakes and the issues with national and international security, it's paramount to take extra precautions to keep products safe and secure, but what exactly is synthetic media? Synthetic media, an umbrella term that describes "any media created or modified by algorithmic means, especially through the use of artificial intelligence algorithms," includes artificially generated voice and video. For example, deepfake Tom Cruise has racked up millions of views on TikTok and opened the door to more mainstream deepfakes, including those for commercial use. In fact, companies including Amazon and Microsoft are currently using synthetic media to build their advertising campaigns, and many other industries are starting to incorporate it into their sales initiatives.

Growing mechanical progressions and quick assembling development are impressively affecting the worldwide store network. For instance, computerized reasoning is assuming control over quality control, Internet of Things (IoT) gadgets and robots are observing assembling and upkeep, and more than 1.9 million robots are as of now conveyed in assembling and warehousing universally. Digital ledger has been proclaimed as a state of the art innovation that will further develop the contemporary store network structure by expanding store network trust, productivity, and straightforwardness. Be that as it may, as promising as digital ledger innovation is, ledger isn't a panacea for production network issues. Cryptography keys consist of two keys, Private Key and Public key.