Merging entertainment with data is a well-known concept. The marketers and content-creators have always focused on strategies that will resonate with the audiences and keep them engaged. Over the past few years, there has been an evolution of AI in the marketing strategies of content creators, brands, networks, etc. AI uses the deep learning algorithms that can digest, asses and contextualize unstructured data quickly to derive actionable insights. AI can analyze millions of pieces of content at a time, with the help of deep learning which is undoubtedly beneficial for the content creators and marketers. Deep learning helps in predicting whether a campaign will be successful even before it starts. Thus marketers are increasingly turning to deep learning algorithms to make better sense of the contents. Read more at: https://www.thedrum.com/industryinsights/2019/04/03/the-evolution-ai-entertainment-marketing

Cyber criminals, also known as hackers, use computer systems to access business and personal information for malicious purposes. There is no doubt that criminals are the most creative people in the world and the development of Artificial Intelligence has only made them stronger. Since the tutorials and tools for its development is widely available in the public domain, AIs use for attacking purpose is hugely unrestrained. Machine learning poisoning is one of the ways for criminals to circumvent the effectiveness of AI. Today we live in a world of chatbots. Most people do not realize how much personal information AI-driven bots may know about them, which makes them easy prey for experienced cybercriminals. Moreover criminals could harness machine learning technology to sift through huge quantities of stolen records of individuals to create more targeted phishing emails. However the biggest fear remains in the fact that the fully unstoppable AI creature will seize the world one day. Thus AI security abuse must be prevented and humans being much better than machines must understand its cause and effect. Read more at: https://resources.infosecinstitute.com/criminals-can-exploit-ai/#gref

A rare hereditary disease is difficult to diagnose. Sufferers have to go through innumerable tests,that take up valuable time of doctors and patients alike with still no definitive result. This additional time delays therapy that could actually be directed to forestall damage. Professors from the University Hospital Bonn and a team of researchers had data of 679 patients suffering from 105 different diseases .They trained a neural network model with 30,000 portrait pictures of affected people and demonstrated how artificial intelligence can be used to perform efficient and reliable facial analysis in cases where the facial structure does show mutations when afflicted with a rare disease. Together with other symptoms and genetic data,it was possible to get accurate diagnosis.

Read more at: https://www.sciencedaily.com/releases/2019/06/190606133805.htm

Business world is now dominated by artificial intelligence and there is no exception in the world of marketing intelligence too. It is found that the future of marketing will be transformed by a powerful, nonhuman force i.e. artificial intelligence. But, even at present, AI and marketing-powered solutions can rationalize your marketing efforts and give you an edge on your competition. Read more at:  https://www.business2community.com/marketing/4-ways-ai-can-improve-your-marketing-strategy-02190347

Employees are the most valuable asset in any organization and your most valuable employees are often the quickest people to leave. The author in this article explores how you can use artificial intelligence to create systems that help meet your employees’ intrinsic needs and build the supportive and challenging environments that employees crave for. Read more at: 

https://it.toolbox.com/blogs/susanowens/5-ways-ai-technology-can-help-you-retain-employees-121818

Nowadays, in business, people are using artificial intelligence and multimedia visual marketing, and these are also connected to the concept of Big Data as every action of internet users take generates a data trail, and the amount of machine-generated data is growing too. So, using data effectively can give businesses an edge in today’s competitive environment as analyzing Big Data helps them to achieve better results in many areas of business with minimum wasted effort and costs. Read more at: 

https://www.business2community.com/big-data/big-data-is-a-powerful-asset-for-business-success-02140458

Careers in machine learning, Data science, artificial intelligence, deep learning and many more are considered as one of the best choices to pursue. Now these technologies and the related jobs are considered one of the hottest and best jobs today. So, here are the list of top 5 languages prevalent in market for data science, machine learning etc.

1. Python

2. R

3. Java

4. Scala

5. C

Read More at https://www.informationweek.com/big-data/ai-machine-learning/5-top-languages-for-machine-learning-data-science/d/d-id/1332311?

Smart Robotics is becoming an evolving field in the area of artificial intelligence. Modern robots have become far more intelligent and adaptable in a continually evolving environment than their predecessors which is attributable to machine perception plays an indispensable role in their development when used in conjunction with more sophisticated machine learning steps.

Data scientists and AI engineers must overcome certain challenges to improve the future of robotics. According to Rewired, there are ways to improve machine perception to fortify smart robots. Treating machine perception algorithms as a passive system coupled with poorly thought on assumptions were the grave mistakes made by programmers. As a remedial procedure, learning as a proactive, multi-sensory process in being borne in mind.  Dependence on antiquated sensory systems have been replaced by new sensory systems to process inputs. According to Russell graves of CoSMoS Laboratory, improved positioning and quality of data forms the building blocks of modern machine perception. 

Read More at: https://www.smartdatacollective.com/vital-role-machine-perception-modern-smart-robotics/

Nowadays, CRM is surrounding marketing, customer service, business intelligence and several other functions. Some CRM systems can also be transformed into enterprise resource planning solutions with the use of apps and third-party add-ons. CRM has come a long way and now can include artificial intelligence, automation, data enrichment through aggregation of contact information from other sources. This article explores some tips for getting more from CRM. They are:

1.       Automate processes and data entry

2.       Clear the clutter of unnecessary data fields

3.       Integrate customer behavior

4.       Use activity management within the CRM

5.       Revisit integrations frequently

6.       Implement automation

Read more at: http://it.toolbox.com/blogs/insidecrm/6-tips-for-getting-the-most-from-your-crm-78266

Nowadays, business is moving faster and getting more demanding due to the increased competition and consumer expectations that come from online and mobile-centred economy. Now, meeting these demands requires managing customer experience at every touch point, and that is in turn putting added importance on automation, artificial intelligence, big data and analytics. CRM is also coming up with some innovations. Here are five of the CRM innovations which are coming up and will help your business to handle today’s market demands. They are:

1.       Automatic Workflow Adjustment

2.       Chatbots and Conversational Interfaces

3.       Automatic Data Entry

4.       IoT Integration

5.       Customization

Read more at: : http://it.toolbox.com/blogs/insidecrm/five-crm-innovations-youll-see-in-2018-78395

Google came with Android O and Apple came up with IOS 11. So, which one’s winning the race? The nutshell answer is Android O. A comparative study has been done to show this. Android O: multitasking, notification dot on the app icon, intelligent text selection, auto-fill, prolonged battery life. IOS 11: pay through iMessage, collaborating speakers, beautified AR effect, live photos, less memory clogging, DND while driving.  Both are equipped with voice assistant, but Google is a step ahead and can recognize objects and you can type queries relating to those objects if you don’t want to speak them. Apple is way backdated with AR and VR as compared with Google who uses AI. Read more at: https://www.entrepreneur.com/article/295854

As AI is moving forward the need for marketing in financial services is diminishing. Generative tools use computers and algorithms and are widely used within Financial Services. So why does that mean financial services marketers are doomed? AI does financial work by simply crunching thousands of data points, factoring in current constraints, predictive models for how things are going to change, and the individual’s goals. AI is making all decisions. Marketers are probably not going to start marketing to AI. More likely, marketers would shift focus to trying to influence the parameters humans input into the AI.  By providing an appropriate media mix to AI we can achieve goals within the budget. AIs are used by both consumers and the companies. Consumers will leverage AIs to optimize their lives and businesses will use AIs to create more personalized products and services. In this future, marketers will ultimately end up marketing to the AIs directly.Read more at : http://www.business2community.com/finance/will-ai-make-financial-services-marketing-obsolete-01855073#LExeE9rhBiBleQLc.97

Nowadays, marketing is not possible without social media and the chatbot has become the newly-adopted social media tool. Chatbots helps in your social media marketing strategy and also increases website traffic and sales while providing Artificial Intelligence assistance which in turn will help you to communicate better. Use chatbots as an analytical tool and optimize it for conversions. Read more at: https://www.entrepreneur.com/article/291997

Salary negotiation is a key to get to the top of the rat race as the World Bank data suggests that 69% of jobs in India are suspected to be taken away by automation. The World Economic Forum predicts 35% of top professional skills today would be replaced in the near future. At present, every person is required to re-assess their skills and re-skill themselves. If automation will disrupt several jobs, there will be technologies like IoT creating many more jobs necessitating critical problem solvers. It is predicted that advanced robotics, artificial intelligence, advanced materials, biotechnology and genomics would be the next frontier of employment. Only with requisite skills in these disruptive fields and a multi-disciplinary approach could empower future job seekers to become critical organizational assets. Read more at : http://economictimes.indiatimes.com/jobs/in-the-age-of-disruption-what-are-the-new-rules-of-negotiating-salary/articleshow/59047575.cms

Subsets of AI are diversifying and algorithms are growing advanced. AI had an alarming impact in many instances. Certain applications of AI are called black box because it is difficult to understand how the result have been generated. Decoding the black box technique involves optimizing a given function in isolation, and sharing it as necessary. This makes the work a lot easier and scales the data. Firms need to make people aware of AI's applications in order to make it more transparent. AI cannot be completely trusted with certain applications. In future, we have to embrace AI and develop trust on it because it has many advantages and black box is a positive step in this direction. Read more at: http://analyticsindiamag.com/making-sense-black-box-artificial-intelligence-trust-ai-completely/

The main responsibility of DevOps and IT operations teams include solving problems and facing challenges which is becoming tougher by each day. This is where real-time and centralized log analytics come to the rescue. It helps them in understanding the essential aspects of their log data, and easily identify the main issues. While Artificial Intelligence (AI) was a big thing a few decades ago, it is now being commonly used. As IT operations becoming more complex, AI is becoming a powerful and essential tool. One solution can be to have a platform that has collected data from the internet about all kinds of related incidents, observed how people using similar setups resolved them in their systems and scanned through your system to identify the potential problems. Cognitive Insights can be introduced, this technology uses machine-learning algorithms to match human domain knowledge with log data, along with open source repositories, discussion forums, and social thread. Read more at: http://readwrite.com/2017/05/15/artificial-intelligence-transform-devops-dl1/

With the increasing availability of data in the present digital age, a new science of opinion mining is emerging. It is based upon the use of Artificial Intelligence (AI) to mine public opinion for sentiments as well as the topics driving that sentiment. This can be carried out in two ways: the first one involves the exclusive use of AI to structure the data, while the second one involves the use of AI along with processing of data through a team of people to verify the data for sentiment and the topics driving the sentiment, since AI could struggle to understand the nuances of human emotions. So, the field of data mining can be used by governments, global organisations, media and businesses to shape their strategies efficiently and, measure the public’s/consumer’s satisfaction of their policies, products, services and brands.Read more at: http://www.business2community.com/big-data/opinion-mining-future-data-analytics-01849821#SoExOgmWJWYF7RIM.97

Business analytics help in taking decisions. Business intelligence involves analysis of prior analysis and is used to support tactical decision making. Machine learning involves processing historical data to make future predictions. There is scope to add applications to deal with consumers. Unless analysis is done in production application the business will not realize efficiencies. Such analysis can speed up daily activities. The prescriptive analysis makes best use of resources by establishing how processes should be executed. Artificial intelligence supports automation of processes and decision. Machine learning is under AI, but more advanced. The main issue is that the analysis and intelligence should be integrated into the working environment. Methods, culture and discipline will always be the key challenges. Read more at: https://www.gooddata.com/blog/key-strategies-for-profitable-business-analytics