#expert networks

[experts-consult-blog]

What expert research says about Machine Learning

Machine learning is a field of study which creates an ability in the computers to learn without being precisely programmed. It is a branch of artificial intelligence which enables the computer’s capability to learn without being detailed programmed and enables them to perform the task intelligently. A complex data process is carried out machine learning by learning from data, instead of following of getting into pre-programmed rules.

Determining and properly understanding the structure and patterns hidden in the data is the main purpose and aim of machine learning. It is largely based on the ability of the computers to go deeper extract the available data even in the absence of a theory of the data structure.

Experts Insights says that machine learning became very famous in the 90s. Machine learning term was coined by Arthur Samuel in 1959 at IBM, who was an American pioneer in the field of computer gaming and artificial intelligence. In 1989, the commercialization of machine learning on personal computers was done. In 2002, Torch, a software library of machine learning was released.

Types of Machine learning-

Various types of machine learning are

Ø Supervised learning

Ø Unsupervised learning

Ø Reinforcement learning

End Users of Machine Learning

End-use industries of machine learning are

Ø BFSI

Ø Healthcare

Ø Government

Ø Automotive

Ø Education

Ø Telecom

Ø Retail and E-commerce

Ø Others

Machine learning mainly focused on the advancement of computer programs which can be switched when they are exposed to new data. It has multiple uses in this era which includes face detection, image classification, speech recognition, antivirus, genetic, signal diagnosing and among others.

In the BFSI industry, machine learning is used in multiple ways. It helps in increasing the sales & marketing, customer centricity and digitalization and among others. In this sector, machine learning also helps in fraud prevention, risk management, loan underwriting, algorithmic trading and among others.

In the healthcare sector, the application of machine learning is increasing day by day which helps to identify and diagnose the diseases and ailments which are hard to diagnose. It is also used in the early drug discovery process, medical imaging, personalized medicine, smart health records and among others.

Machine learning is also helpful for the government to deliver better, cost-effective and customer-friendly services.

Industry experts of the automotive industry believe that machine learning can help them to achieve marketing goals. It is precisely connected with product innovations, such as self-driving cars, parking, and lane-change assists.

Machine learning in the education sector helps the institutions in adopting cloud technology which has helped in reducing various operational costs. Machine learning is promising fraud detection essays, individual grade analysis and among others.

Insights from experts say that machine learning is being used in the telecom industry to enhance their customer service. Machine learning in telecom industry plays a vital role in network performance data, social media data, fraud mitigation, identifying and improving server application and amongst others.

Experts from Retail and E-commerce industry have analyzed that this industry has grown and improved a lot with the deployment of machine learning as it allows the e-commerce business to create a personalized customer experience. It even helps the retailers in reducing customer service issues before they issue.

E-commerce search results are improved every time a customer shops on the website based on their personal preferences and history with the implementation of machine learning in e-commerce and retail industry.

Other end users of machine learning include manufacturing industry, robotics, transportation, oil and gas and among others.

Machine learning is widely being adopted by the industry experts for making informed decisions for achieving the objectives and goals of their businesses and eases their customer service operations and provides customer-centric services.

The global machine learning market was valued at the US $ 1.29 billion in 2016 and is anticipated to reach at a value of US $ 39.98 billion by 2025.

Major factors driving the growth of machine learning market are technological advancements and mushrooming of data generation.

Unavailability of skilled machine learning professionals is the major factor restraining the growth of this market.

The adoption of machine learning by the increasing demand for intelligent business processes and rising adoption of modern business applications and tools is foreseen to create lucrative opportunities for the growth of machine learning market.

Various challenges faced by the industry experts for the adoption of machine learning are the inaccessible data, its inflexible business model and the affordability of organizations as it requires tremendous revenue charges for a company for the implementation of machine learning.

Major players functioning in the machine learning market includes

1. Alesco Data

2. Ant Works

3. HireIQ Solutions

4. Knexus Research Corporation

5. Pienso

6. Anaconda

7. Aspen Technology

8. Kim Technologies

9. Microsoft Corporation

10. Intel Corporation

11. Google Inc.

12. HP

13. SAP SE

14. IBM

15. Amazon

Future Insights

Expertsconsult believes machine learning will eliminate 50% of the supply chain predictions error, reduce transportation cost by 10% and cut administrative expenses by 40% in the future. Machine learning will also minimize waste and drive unequaled efficiency by eliminating bottlenecks, streamlining inventory management, optimizing production and logistics. According to expert’s surveys, it is predicted that if machine learning is coupled with big data and healthcare app development can generate a value of $100billion per year in healthcare and machine learning is also proceeding for preventive healthcare in this new era. According to the analysis by industry experts, it is believed that machine learning has the potential to create an additional value of $2.6T by 2020 in sales and marketing and a value of up to $2 T in manufacturing and supply chain planning.

Conclusion

The primary reason for the adoption of machine learning platforms is to improve customer experience and it is being adopted by 82 % of marketing leaders to improve every aspect of their personalization strategies.

[projecthillgate]

What is the Difference Between an Expert and a Consultant?

As COO at Hillgate, and having spent time as an executive at an expert network firm and as a strategy consultant, one of the questions I am frequently asked is how to decide whether a project is more suitable for an expert or for a consultant. Here are some guidelines to help you decide:

 1.    How much of the answer is already known?

Expert networks such as Gerson Lehrman Group and Clarity.fm typically provide consultants by the hour. When you have a good understanding of the answer, they are a good option to test your logical assumptions with someone who has ‘been there, done that and made the mistakes’. An expert is the efficient way to learn the accepted answer.

 If you are still at the hypothesis stage, it may be better to engage a consultant via Hillgate. A 2+ week engagement can provide you with a comprehensive analysis of the market landscape, best practices and options, which you can use to determine how best to innovate and accelerate growth.

 2.    How broad are the topics you are trying to answer?

Experts are best used to answer specific questions. Since you typically engage someone deeply experienced in a very specific area, focus on the expert’s narrow area of expertise.

 If you are looking at a broader set of topics, engage a single consultant with solid generalist training. He or she can combine primary and secondary research and manage the overall analysis so that you can focus on the big picture. Particularly when preparing to make a significant investment (e.g. launch a new product, enter a new market), engaging a consultant to complete diligence can provide a great second opinion and additional insights.

 3.    Do you need advice or hands on help?

This should be the easiest option to decide. Experts provide advice – they answer questions and provide opinions based on their practical experience.

 When you need someone to ‘get their hands dirty‘ and help you do the actual research and analysis, a consultant can be more helpful. They are trained in building the Excel models and creating Powerpoint presentations – enabling you to focus on preparing for the leadership team meeting and the strategic decision-making.

  At the end of the day, all you really need is to the best person to help you deliver on your goals. To achieve that, it is important for you and your advisor to build a strong relationship - and for him/her to relate to your current need. [1]

 [1] Ting Zhang recently conducted an interesting study into how to get an expert to empathise and meet you at the right level of insight. More details here.

[davemoon]

Accountability in Crowdfunding - Transparency and Judgement

For all its breakthroughs, crowdfunding has realized a slow accumulation of hard truths. Things don’t always go so well. Production gets delayed. The project founders may not be prepared to handle a boisterous and demanding crowd. And then come the cries of fraud and failure. The excitement over seeing creative projects close millions of dollars of funding through Kickstarter and IndieGoGo has given way to the challenge of bringing those ideas to market and introduced the problem of, at times fumbling, execution. NPR raised the stakes and framed the challenge in terms of refunds and liabilities. If funders give money, are the creators legally liable? Do they need to provide refunds? To their credit, Kickstarter responded with a blog post - yes. Accountability is paramount to the funding process, but it’s a qualified yes. Though founders are legally obligated to provide refunds for any benefits promised and unfulfilled, “We hope that backers will consider using this provision only in cases where they feel that a creator has not made a good faith effort to complete the project and fulfill.” Accountability is important, but it’s accountability to a good-faith effort. No one wants to miss their production deadline, but it happens. To assess whether they were operating in good faith, founders need a communications channel with which to set expectations, and the market must exercise good judgement to assess failure or success. These two elements, crucially, are missing on the crowdfunding platforms. Founders don’t have the best communication channel to their funders. They’re limited to the project page, a comments section, and general email updates. None of these are particularly well suited to sketching out a timeline of tasks, dependencies and deliverables for their project. Indeed, the comments format is comically unsuitable, leaving a trail of missed connections and missing context. The still-open Auris bluetooth adapter for the Bose Sound Dock project comments are awash with unanswered compatibility questions and even a question regarding intellectual property and the underlying legality of the project. Unresponsiveness aside, the comments page could use an update. Rather than a continuous stream of messages, the comments page should provide a snapshot of the project’s current status and also tell the story of the project’s history. The experience could be taken still further and also provide a forum for founders to marshall the expertise of their funders for the success of the project. These kinds of changes could improve the satisfaction of the funders and success-rate of projects, while also providing the transparency to establish whether the founders were operating in good faith. Possible paths to take include the following.

Timeline - The comments page should include a timeline that details the project history and plan. The key features of the project history are milestones and founder-updates. The milestones for design projects, for example, could begin with the Kickstarter launch, followed by the successful funding, and then a series of concrete production goals, such as the steps that take the project from prototype to production. The presentation founder-updates should illustrate a regular communication with their funders on these goals.

Founder-Thread - Founder updates and messages are important. Why not list them on their own, rather than mixed in amongst the, at times, many other comments? Pebble has more than one hundred and seventy pages of comments. Give the funder a view that shows the founder’s comments. If anything stands out, they can zoom to that point in the conversation.

FAQs - The Hex Bright programmable flashlight has more than forty-four pages of comments. Shouldn’t salient questions receive their own thread? Couldn’t funders and founders tag questions and answers around specific issues?

Experts - Each fundraise not only collects money, it collects people. Those people have expertise and experience that could be invaluable in the development of the project. Let founders put a call out for expertise. Give funders a chance to contribute their expertise.

[thedailycaveat-blog-blog]

Hedge Fund Tied to Expert Network Insider Trading Investigation Hires Counsel From Expert Network Likewise Tied to Insider Trading Investigation

Well, you figure it won't take much to get him up to speed, right?

See: Business Insider --Coatue Just Hired A White Collar Crime Lawyer From An Expert Network

[thedailycaveat-blog-blog]

Primary Global Employee Pleads Not Guilty on Insider Trading Charges

James Fleishman is one of a number of people arrested arrested in connection with the government's insider trading investigation of expert network consultancy, Primary Global. Fleishman as been accused of acting as a middle man, setting up meetings that allowed executives to pass on insiders tips to Primary Global's hedge fund clients.  

A recap of others arrested thusfar: 

Robert Nguyen, a Primary Global consultant focused on the semiconductor industry.

Dan L. DeVore, a global supply manager at Dell, who has also admitted to selling secrets to research firm, Guidepoint Global.

Mark Anthony Longoria, a manager at AMD who sold Apple iPhone and iPad launch secrets.

Winifred Jiau, who offered inside information about a variety of firms, was arrested just as she was attempting to flee and almost served as an FBI witness.

Walter Shimoon, a manager at Flextronics, which makes Apple batteries and charging devices.

Manosha Karunatilaka, of Taiwan Semiconductor Manufacturing.

Raj Rajaratnam of hedge fund, Galleon Group (which has its own troubles in the government's broader probe of insider trading) and of America's richest people. 

According to the SEC's newly unsealed complaint, Longoria, DeVore Jiau and Shimoon, who moonlighted as "consultants" for Primary Global were in possession of material non public information, which was them passed through the meetings set up by Nguyen and Fleishman.  Along with Fleishman both Robert Nguyen and Dan L. DeVore have also plead guilty.

Including the muti-level mess at Galleon, at least thirty people have been arrested as a part of the multi-year state and Federal insider trading investigation with criminal charges fined against 21 of those and guilty please from nine, producing eight cooperative witnesses.  In all, as many as eleven separate hedge funds may have benefitted from the expert services insider trading ring.  

With the SEC's complaint now unsealed and civil as well as criminal trials proceeding apace, nothing about this story is slowing down any time soon.

[thedailycaveat-blog-blog]

Taken Aback By the Government's Insider Trading Probe?

Not if you've been following The Daily Caveat for any length of time...  This investigation has been in the works for quite some time and some familiar names, like Gerson Lehrman, have recently re-emerged. The early heat had come from the NY AG's office, which sent out subpoenas back in 2007 and there was a brief little mention of a parallel Federal probe.  That shoe, it seems has well and truly dropped.