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Blockchain are certain to disrupt almost all industries fundamentally. Though there are technical issues, the idea of utilizing a blockchain to prove ownership, to prevent double spending and to establish trust and transactions in an otherwise trust-deficient world, is gaining excitement and acceptance. More and more enterprises are getting curious about the blockchain and are willing to start investing in learning, prototyping, and building on top of the blockchain technology. Starting out with the blockchain requires investment in a building the domain expertise, establishing the identity, establishing the infrastructure and deciding the blockchain that the enterprise wants to work with. Among these decisions is the question: Should the enterprise choose a public blockchain or a private blockchain. Both have advantages and disadvantages and the question can often come down to what are the short term goals and potential applications that the enterprise wants to build on the blockchain. Public BlockChains The default option when considering blockchains is the public blockchain. This is the blockchain that is truly decentralized, leverageable for any type of transaction and in the case of the Ethereum blockchain, offers SmartContract authoring capability that makes the blockchain very attractive for building contracts that reflect the needs of the real world. However, for an enterprise deciding between public or private contracts, there are some considerations that require attention. Speed and Scalability Public blockchains tend to be slower as they are limited by the number of transactions that can be verified every second and confirmed every 10 minutes. There are several efforts underway to make blockchains faster and more scalable however those will take time to get implemented. Speed and scalability will continue to be an issue and contracts and applications that require instant or near real time execution will suffer from this lack of speed and scale. Se

The Occupational Safety and Health Administration or OSHA is dedicated to the health and well-being of employees while on the job. Day in and day out employees are exposed to potentially dangerous situations based upon their specific job functions. Whether a person is employed at a manufacturing facility, an auto body shop, or within a large warehouse, OSHA regulations aim to provide the warnings needed to keep hazards at a minimum and keep employees informed about their surroundings. One of ways in which employees are kept informed about the hazards and dangers within their work environments is through the usage of warning labels. Types of OSHA Warning Labels and Signs The term warning label or sign can be used interchangeably in regards to OSHA's recommendations for hazard warning. There are basically three types of labels or signs outlined within OSHA 1910.145 and they are used to indicate danger, caution, or general safety instruction. Danger Sign/Labels: Danger labels or signs should feature the colors or red, black, and white. Employees should be informed that whenever danger signs or labels are posted they should exercise extreme caution as many hazards are immediate. This does not mean dangers are possible, it means they are imminent if certain things were to happen. Caution Sign/Labels: Any signage or labels indicating caution should feature a yellow background with black lettering. Caution labels or signs should be used to inform employees about potential hazards. This is unlike danger signs, since dangers signs indicate certain dangers that ARE there, while caution indicates that hazards are just simply POSSIBLE. Safety Instruction Sign/Labels: The standard background should be white, with black letters upon the white background. In addition, on the panel, green with white letters may also be used. This type of warning label or sign is used when general information related to certain safety practices is available. Furthermore, OSHA indicates in 19

In the business world, there is a constant need and desire for improvement. It doesn't matter whether a business specializes in the market of rare auto parts or in making the best enchiladas. The plain and simple truth is that improving business practices to meet the ever-changing and diverse needs of society is essential to the success of any business endeavor. However, with all this change and improvement often comes a little struggle. Sometimes business processes are changed so radically that employees struggle with the changes if they are not adequately informed about what changes are taking place or how the changes actually benefit the specific process or end product. Furthermore, in some cases the problem is not with the employees at all, but instead embedded within the actual process changes. When looking into making improvement changes, it is important to really take the time to evaluate the changes fully to make sure that they are win-win for both the employees and the desired business objectives. Employee Involvement In the improvement process, there are often many things to consider especially such as metrics, data, resources, etc. However, it is important to make sure that employees are also considered within the grand scheme of things. There are times when businesses make essential changes that are needed to stay current with the changing times, but often neglect to involve the actual employees in the process of determining changes, or in the reasoning why specific changes were made. This can leave employees feeling a bit resentful and also leave processes lacking in certain important fundamentals. For instance, the top managers in a business make the decision to improve a production line within the factory because many of the machines were getting older and not handling the work as effectively as needed. In order to update the production line to new standards, new machines were installed and tweaks were made to previous processes in order to help

We are a different AI company. See how our LearnCloud brings together your entire enterprise to operate on the same "information plane" towards an exponential increase in efficiency. Jenny is responsible for customers at Acme Corp Jenny feels she is driving blind. She realizes the ground truth but often it is too late. The information is spread across multiple applications & systems. Even when available, it does not help her look into the future so that she can act & save the day Sarah is a Support professional at Acme Corp Sarah feels she has her hands tied behind her back. She has to manually process each & every issue. Her job is tedious and inconsistent. She is not able to leverage patterns across issues & across support professionals. John is a salesperson at Acme Corp John is frustrated with antiquated tools & late arriving insights He has to manually scour the internet for information about his prospects & their changing strategies. He has to talk to many people to understand the state of the customer. By the time he understands the current state, it is often too late to prevent abandonment or drive the expansion People like them encounter these problems all the time which causes frustration and attrition for them and their customers. How does this happen?

Success with AI is heavily influenced by the data maturity of an organization i.e. their ability to procure, clean, curate, store and analyze data to power value generating applications. A data-mature enterprise know what data it has, knows what the data means and can ensure that the data is accessible to whoever needs it. Unfortunately, the past few years, driven by the big data hype, have encouraged enterprises to focus on updating their data infrastructure to leverage new big data technologies. With a lot more data now available, enterprises already stuck with massive data storage costs, are being forced to choose between storing data that might eventually be useful for stabilizing, if not reducing their storage costs.

Transforming into a tech company has become top of mind for executives in all major industries. It is clear that modern technology will fundamentally alter what and how business is done in every domain, sector, and industry. This has led to a call to arms in every enterprise to understand how they can transform into a tech company. The Tech Company Magic Tech companies have fine-tuned the art of bring new digital products and services to the market, quickly, efficiently and effectively and understanding customer feedback to iterate and improve. This capability makes them incredibly agile and leads to faster experimentation that is cheaper and involves less risk. In turn, this enables them to bring new capabilities to the market and even if all do not succeed or get traction, a few do and that drives innovation, customer satisfaction, and growth. From the outside, tech companies appear to be massive juggernauts that are unstoppable and able to crush everything in their path. The 'Non-Tech' Technology has been leveraged in every sector and industry, however, it has almost always been treated as a means to an end, something that is required but never the real value driver for the customer. This has led to the typical organizational structure in enterprises into "Business", "Operations" and "Information Technology". The "Business" arm generates value for customers, the "Operations" team carries out the requirements of the Business team and the "Information Technology" team provides the systems (databases, network and compute) required to "keep the lights on" for the Operations and Business Teams" This structure served enterprises well in the last decades as customers did not have an alternative to directly working with the enterprise and this fortified the value supply chain and also established a hierarchy of sorts within the enterprise where the business looked down upon operations who looked down upon technology. The purpose of

Much has and needs to be said about an enterprise's AI strategy. Artificial Intelligence or AI is considered a fundamentally disruptive technology similar to the steam engine, electricity etc, a technology that will be pervasive and absolute in its impact on the world and its inhabitants. The ability to find hidden patterns to predict the future or detect a behavior has massive implications across the world, in every industry, sector, and domain. When faced with this realization, enterprise's can find themselves stuck, paralyzed and unsure about how to proceed. The field of AI is decades old already and the early success stories have been practicing AI for multiple years already with the tech industry leading the way. How can an enterprise that has no experience and competency in this area let alone lead the technology or even leverage it appropriately to drive business value? When developing the AI strategy, two ideas are paramount. First, this a fundamentally disruptive technology and the enterprise will need to establish it as a core competency for the foreseeable future. Not doing so will not be an option. Second, a long-term plan to success is superseded by the need to drive quick wins and small successes not only to build confidence but use real-world experience to develop and hone that skill. The Short-Term AI Strategy The short-term AI strategy should focus on driving immediate business value through enhanced customer experiences that leverage any field of AI be it machine learning, deep learning, natural language processing etc. Driving the usage and deployment of AI in front of an end user making them smarter, productive and better informed can pay rich dividends by not only helping the enterprise can real-world experience, but it can also give a perception boost to the company as being innovative and cutting edge. However, most importantly, this can highlight and promote the success and potential of AI in the enterprise and encourage a snowball eff