January 19, 2018
Business And Artificial Intelligence Learning
You know when you learn how to grow your business it isn’t just a worthy goal; growing your business is often a necessity for your business’s survival and your economic well-being. And what can you do to get your business beyond the bare sustenance level? What can you do to turn it into the income-generating powerhouse you envision? You can try one or more of these growth strategies. All have been successfully used by other businesses and, with some planning and investment, will work for you.
According to the Project Management Institute, project managers are change agents who use their skills and expertise to inspire a sense of shared purpose on a team. They work well under pressure and can shift between considering the “big picture” and the focusing on the details. A project manager can be an asset on every project that involves multiple people, whether it’s a home renovation project, a small business collaboration or a personal project.
A good project manager is highly organized and has an exceptional ability to follow through. If you are considering starting a project management business, here is a look at the pros, cons and where you can get more information on how to get started.
When you think about how to grow your business, the first thing that probably comes to mind is getting new customers. But the customers you already have are your best bet for increasing your sales; it’s easier and more cost-effective to get people who are already buying from you to buy more than to find new customers and persuade them to buy from you. See 6 Sure Ways to Increase Sales and 10 Low-Cost Ways to Promote Your Business for more.
The Artificial Intelligence (AI) and Machine Learning are projected to become mainstream technologies in the coming years, and are definitely already having a big impact across many industries. How exactly is this happening? How are Data Scientists using their skills to develop better Machine Learning algorithms? Where are these innovative technologies going in the future? Andrew Charlton an economist and co-founder of AlphaBeta. author of Fair Trade for All, Ozonomics, Man Made World, and Dragon’s Tail, has had a big impact on the Australia’s economy.
And you know with the rise in the implementation and usage of once revolutionary technologies/trends like Big Data, the Internet of Things (IoT), or the Cloud, Machine Learning (ML) and now Deep Learning (DL) are gradually moving into mainstream business corridors. Traditional business graduates can now think of becoming a Data Scientists as well, since many University programs are offering these courses as part of their business curriculums. The modern Data Scientist, armed with the power of an open source, algorithm economy, are becoming important parts of numerous organizations around the world.
The Harvard Business Review article titled How AI Fits into Your Data Science Team claims that Artificial Intelligence and Machine Learning will soon take the status of the ICE engine by bringing in sweeping changes to our everyday lives. The transformative power of AI and ML have already been perceived in customer service (digital assistants), in telemedicine (assisted patient care), in banking and finance (robot sales representatives), or in manufacturing (robot assembly-line workers).
When you move into a business office
Well, as AI technologies gradually started moving toward statistics-enriched solutions, the biggest stumbling block that surfaced was limited data. The recent emergence and rise of Big Data, IoT, and Data-Technologies-as-a-Service all jointly contributed to the meteoric rise of Artificial Intelligence and a widespread, packaged Machine Learning algorithm culture.
And the biggest beneficiaries of this culture are the mainstream business users, who can now begin to accomplish their tasks without the help of a Data Center, and in some cases even Data Scientists. However, the last statement in no way indicates that Data Scientists will soon become redundant. In fact, Data Scientists will be required to intervene when advanced data solutions or unique data solutions must be designed to accomplish complex business goals.
A Forbes blog post titled The Rise of AI Will Force a New Breed of Data Scientists suggests that the new role of the Data Scientist will be more of an facilitator, rather than that of a data cruncher. The Data Scientist may evolve into Machine Learning expert, stepping in when packaged models fails to deliver