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What are the latest innovations in the Artificial Intelligence in Construction?

MMS Founder

Article originally posted on Data Science Central. Visit Data Science Central

 The Artificial Intelligence in Construction Market size is estimated to generate a revenue of $2,642.4 million by 2026 with a CAGR of 26.3% in the forecast period.

Artificial Intelligence is a system that enables to achieve the task in seconds where a normal human being requires high intelligence to complete the same task. Artificial intelligence includes decision-making, speech recognition, translation between languages, visual perception and many more. All these activities can be performed with the use of historical data. With the use of artificial intelligence, companies can have a better design for building with generic ideas. By using some software, they design and explore all the difference to a solution and can generate the alternative design in the minimum time which a normal human being can take a lot of time according to the intelligence level.

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The cost involved in artificial intelligence is very less. Several companies hire professionals by spending so much of time and money. The professional takes a lot of time based on the intelligence to complete the task, but with the help of artificial intelligence and small team one can do the same work within minimum time by gathering the previous data of the company which gives the accurate result. Many companies have initiated many automated vehicles and devices which can finish the construction work at the earliest and improve the work competence of the workforce.

To work with artificial intelligence one must have sound knowledge with regards to the domain and also have technical knowledge. The availability of the skilled workforce is considered to be the biggest constraint for artificial intelligence in the construction market.

North America accounted to have the highest share in the global artificial intelligence in the construction market. North America is estimated to raise at a CAGR of 25.4% by generating a revenue of $898.4 million by 2026. Due to the rapid advancement in technology and the increasing government initiative are expected to drive the artificial intelligence in construction market for North America. AI in Construction Market forecast that the Asia-Pacific regional market has the highest growth rate. Asia-Pacific market is likely to rise at a CAGR of 28.9% by generating a revenue of $684.2 million by 2026. Increasing investment in infrastructural construction like supply chain management, risk management, and project management. The increasing demand to create smart cities in this region is encouraging the companies to invest in artificial intelligence which will give boost to AI in Construction market.

AI in Construction Market players include, Inc., Dassault Systemes SE, Volvo AB, Doxel Inc., NVIDIA Corporation, Building System Planning Inc., Komatsu Ltd, and Autodesk, Inc. among several players.

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Using Language and Developer Friendly Data Structures with Couchbase

MMS Founder
MMS Rags Srinivas

Article originally posted on InfoQ. Visit InfoQ

The recently written blog outlines how developers can use data structures (such as lists, maps, etc.) with Couchbase 7.0 using the respective language APIs/SDKs.

Although, like most NoSQL databases, Couchbase was originally intended as a data store for Key/Value pairs and then for Key/Document (documents usually in a JSON or similar format), they can now be used with data structures making it more developer friendly. Most NoSQL databases have also evolved to support more language friendly data structures originally intended for simple Key/Value and Key/Document pair(s) scenarios — the onus was on the programmer to covert from the respective data model to data structures and vice versa requiring to write a lot of boiler plate code.

Besides documents and counters, Couchbase language APIs now supports the following foundational data structures.

  • Lists
  • Maps
  • Sets
  • Queues

Internally, Couchbase organizes the data structures as JSON documents, distributing it across the cluster and making it available as a language native data structure via the respective language APIs. Some examples below illustrate how to use data structures with the Couchbase Python SDK.

We will start by looking at some queue examples using Python. The Doc ID below is fibonacci and we push the values 0,1,1 respectively as illustrated below.

cb.queue_push("fibonacci", 0, create=True) # [0]
cb.queue_push("fibonacci", 0) # [0, 0]
cb.queue_push("fibonacci", 1) # [0, 0, 1]
cb.queue_size("fibonacci") # 3
cb.queue_pop("fibonacci") # 0 (in FIFO order)
cb.queue_pop("fibonacci") # 0
cb.queue_pop("fibonacci") # 1

Likewise, examples below show using the List APIs.

cb.list_append("qbs", "tom", create=True) # ["tom"]
cb.list_prepend("qbs", "josh") # ["josh","tom"]
cb.list_append("qbs", "patrick") # ["josh","tom", "patrick"]
cb.list_append("qbs", "aaron") # ["josh","tom", "patrick", "aaron"]
cb.list_size("qbs") # 4
cb.list_get("qbs", 0) # josh
cb.list_remove("qbs", 0) # ["tom", "patrick", "aaron"]
cb.list_get("qbs", 0) # tom
cb.list_get("qbs", 2) # aaron

The respective values can be JSON documents as illustrated below with the Map API.

cb.map_add("quarterbacks", "bills", {'name': 'Josh Allen', 'age': 24}, Create=True)
cb.map_add("quarterbacks", "bucs", {'name': 'Tom Brady', 'age': 43})
cb.map_add("quarterbacks", "chiefs", {'name': 'Patrick Mahomes', 'age': 25})
cb.map_add("quarterbacks", "packers", {'name': 'Aaron Rogers', 'age': 37})
cb.map_get("quarterbacks", "chiefs") # {'name': 'Patrick Mahomes', 'age': 25}

More data structure APIs for Python is available in the Data Structures docs and is summarized below.

Image Source: Couchbase Blog

Similar APIs are available for other language SDKs supported with Couchbase.

In summary, Couchbase and the accompanying language APIs makes it’s easier for developers to persist and retrieve data structures with the data structures APIs. A Cheatsheet of the APIs and the docs are available to getting started and incorporating them in applications.

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Creating Data Center Backup and Recovery

MMS Founder

Article originally posted on Data Science Central. Visit Data Science Central

Backing up your data allows you to keep your operations running, preserve customer and sales data you need for business planning or a marketing strategy development. However, not too many business owners are familiar with this process which is rather simple to perform even though it offers a wide array of different methods, some of which should be combined for maximum effectiveness.

In our current article, we’ll go through different types of backup and technologies that allow us to protect our data.

Types of backup

There are three main types of backup that we can perform, each of them is best suited for different user requirements. Depending on what we wish to achieve we might go for:

  • Full backup
  • Incremental backup
  • Differential backup
  • Real-time backup
  • Bare metal backup

The full backup is the most basic type of data preservation. It includes creating a copy of all the data available on the server. Full backup takes a lot of time and storage space, so it’s mostly performed just once when all systems are set.

Incremental backup means backing up only those files that have changed since the last backup. Imagine running a writing service and you wish to make sure that all information and data you share with your assignment writers are available and correct at all times. This type of backing up would make sure that every change gets a secure copy.

Differential backup is the type of data protection that backs up a piece of information the moment it’s changed back to the last full backup point that the user chooses.

Real-time backup tracks changes in your files as they happen and updates the backup information accordingly.

Bare metal backup allows backing up the entire server in a way that lets us restore all the lost data even on hardware that has no software or even OS installed. This is a great option in case there’s physical damage and new pieces of hardware are needed.

Local backup

This method of data preservation is somewhat outdated because backing up an entire server to a local physical drive would take too much time and space. In addition, the recovery process would take too long which is why this method is not recommendable for data centers. However, a friend of mine at EssayWritingLand told me he uses a physical drive to back up his work because textual files don’t take too much space and that makes disk backup a perfect option.

Cloud backup

This is a much faster method to protect our data and much easier to manage since cloud backup and recovery solutions often come with a series of features that automate and facilitate data backup and recovery. This method includes sending copies of files to cloud storage over the internet so upload and download demand fewer resources.

Types of data recovery

There are many ways to jeopardize the integrity of your information, depending on the type of issue and the amount of data that need to be recovered there are several types of data recovery:

  • File recovery
  • Volume recovery
  • Bare metal recovery
  • Instant recovery

File recovery means getting back a lost or corrupt file or a group of files. Files could be corrupted by malware or accidentally changed or deleted by a user.

Volume recovery is a great option when we need to retrieve a large number of files and folders, especially if we wish to preserve previously granted permissions and folder settings.

Bare metal recovery is a type of data retrieval that happens when a new piece of hardware is installed due to an equipment upgrade or a disaster. This type of recovery allows us to restore our entire server to a specific point in time even if our hardware has no software installed.

Instant recovery is one of the most advanced types of data rescue that could be achieved through local or cloud backup. In this process, data is being backed up continuously, and when there’s an issue the system redirects to the most recent backup, allowing the server uninterrupted work until the original data is restored.


The best option is to balance between the amount of time your business can afford to stay offline and the amount of data you can afford to lose, in most cases, this means how far back you must keep your data. Measure carefully both sides of the scale to benefit your business needs and secure the optimal data protection strategy. This guide should help you understand some main questions that worry those among us who lack technical expertise but have the need to personally take care of their data safety.

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InfoQ Live: Practical Ways To Integrate Observability Into Your Distributed System Architecture

MMS Founder
MMS Adelina Turcu

Article originally posted on InfoQ. Visit InfoQ

On Feb 16th, InfoQ Live, the one-day virtual event for software engineers, will explore practical ways you can use and integrate observability into your distributed system architecture.

By Adelina Turcu

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Why You Should Use Big Data Analytics in Recruitment

MMS Founder

Article originally posted on Data Science Central. Visit Data Science Central

Big data, a term that describes a huge volume of data that inundates businesses on a daily basis, has transformed many processes in numerous different industries. The way big data works in business is that it gets analyzed to reveal patterns that weren’t previously recognized and provide companies with more insight into a certain process, human behavior, or whatever you are searching for.

Today, big data analytics has become a crucial part of business even for small and medium-sized companies. The main reason why this has become so popular is that it gives businesses a bigger chance of success. It lets them know marketing trends before others discover them. It can also show them how they can improve the efficiency of their manufacturing processes. Similarly, big data has been proven to be very effective in the world of recruiting.

Traditional vs. Predictive Hiring?

Traditional hiring is a pretty straightforward process. All you have to do is post an ad somewhere, wait for people to apply for a position, manually screen their resumes, and conduct interviews. Although this type of process isn’t going anywhere soon, in most cases it isn’t the most effective way to find good candidates for a position at your company.

The main downside of the traditional hiring process is that you have to use only the information provided by candidates and your intuition to determine whether they’d be a good addition to your company. Predictive hiring, which is rotted in big data analytics, takes a different approach. It focuses on analyzing historical data to make predictions about future behavior.

How You Can Use Big Data Analytics in Recruiting

What if you could be certain that you found fitting candidates for a position before you even start interviewing? Let’s say that your goal is to turn your company into one of the best essay writing services UK. When you aim to provide such a specific service, you need to have excellent writers in your organization.

If you decided to find candidates through a traditional hiring process, there’s a good chance you’d hire at least one person that isn’t skilled in writing custom essay papers despite having relevant qualifications. That’s because resumes are usually one-dimensional and don’t provide you with a complete picture of candidates.

What makes predictive hiring a better process is that it focuses on identifying the talent level and skills candidates possess instead of their official certifications. It’s worth noting that a concept like big data wouldn’t be possible if it weren’t for the widespread popularity and usage of the internet. Nowadays, it’s normal for a person to have accounts on several different social media platforms.

Recruiters are able to collect data from social media profiles in order to create a better picture of a candidate before the first interview. Some of the best platforms where you can find useful data about candidates include LinkedIn and Quora. If someone is frequently helping college students with academic writing on a website like Quora, it’s a good indication that they’d be a good addition to your essay writing service.

Another thing that big data analytics can do is help you learn more about the applicants’ personalities. You can extract and analyze data from pre-employment assessments to get a better understanding of a candidate’s skills and personality. This can help you determine whether they’d fit with your company’s culture.

If you aim to provide UK best essays to college students, you’ll need to know that they can provide excellent services. In this particular example, college students rely on quality help as anything less than that may cost them a lot. The last thing you want to do is hire a bunch of dissertation writers that can’t even craft an essay paper. Big data analytics can help you avoid situations like this by providing you with a complete picture of an applicant’s previous performance reviews.

If a candidate has any type of online presence, regardless of how small it is, big data analytics will find and analyze it to provide you with a better understanding of potential candidates. In our example of starting an essay writing service, it’s imperative to look for people with university diplomas. However, if you were to look for a programmer for an IT firm, you could use big data recruitment to find experts in this field who might not have a diploma.

Benefits of Big Data Recruitment

Recruitment can be quite a costly process, especially if you have the task of filling several different positions at your company. Expenses can be very high if you need to repeat the recruitment process due to the bad quality of new hires. One of the main benefits of big data recruitment is that it increases the quality of new hires and minimizes hiring mistakes. Recruiters are able to take a more strategic approach if they use big data analytics to fill a position.

Another benefit of predictive hiring is that it helps you to create a more consistent workforce. Knowing the personality traits of a candidate before they first step foot in your building can make it easier for you to decide whether to hire them. If you and your recruitment team are on a tight deadline, you can also use big data to analyze and predict the speed of hire. Finally, you can rely on big data analytics to monitor and embed diversity into the hiring process.

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The Role of Big Data in Human Resource Management

MMS Founder

Article originally posted on Data Science Central. Visit Data Science Central

The most successful business organization understands the role and importance of HR to the organization, especially when it comes to acquiring top talent and keeping them. To remain competitive and at the top of their game, HR departments are now looking to leverage big data analysis. This way, they will be able to quickly identify the best performers before others go ahead and hire them. This will also ensure that they can keep the employees engaged and happy and improve their employee retention level.

The advancement of technology to handle big employee data is continuing to advance. As a college paper writer states on the write my dissertation platform, it’s only a matter of time before this competitive advantage becomes normal. The fierceness in the job market and the candidate-driven approach that many companies take mean no better time for HR professionals to embrace data analytics.

There are several roles and advantages that big data offers the HR departments. Some of these are:

Reduces the risk and cost associated with a bad hire

A bad hire can be costly for the business in many ways. Many businesses invest their time and resources into training new hires. If they turn out to be a bad hire, they would have wasted the resources spent on them. Not to mention the cost of sending them off, looking for a replacement, and affecting the business operation.

A bad hire is bad for any business. This is why HR managers are now turning to analytics to help them choose the right candidate. If they’re able to find the best candidates then, the company can save the cost of recruitment, productivity loss, training expenditures, loss of clients due to negative experience and reviews about the employee, etc.

A bad hire is too costly a mistake for companies to make. That is why they use big data to reduce the possibility of that mistake.

Improve the rate of retention

It is more profitable for a business to retain its staff than to hire a new one regularly. Matt Law, an author who writes essay review service for do my assignment Australia platform, states that a business with a low employee retention rate is very likely to suffer. This is very much the truth.

Once an organization makes a hire, they tend to invest in that person the energy, time, and resources needed to bring them up to standard. However, when they resign, what happens? They have to start the process all over again and continue that cycle.

By using big data technology, it is possible to spot employees who are likely to walk out on the company by going through their job performances, employment history, payroll data, profile updates, and other online activities.

If the algorithm finds that the employee is a high-value employee, you know you have to try and retain them. This might mean that you offer them a more challenging role within the organization, increase their wage, etc. This is an effective strategy that many top companies use, and it works for them.

Predicting performances

Big data makes it possible to predict the performances of employees upon or before hiring them. For instance, HR personnel needs to determine if the person they are hiring can fit into the work culture and offer a satisfactory work level like other employees. Having to rely on gut feeling in cases like these isn’t reliable. It is also extra work if they have to compare individual prospects to the current set of top performers employees in line with the job requirement.

Instead, HR departments can use analytics to build a high performer profile with the employee records. This will make it easy to headhunt for specific targets. This will make it much easier to find and pick out the best talent.

There are several freelancing platforms for assignment help that already use this model. These predictions are very strong and significant, so you can use them in evaluating layoffs, promotions, and other job openings within the company. This will help the organization save its resources and time on recruitment.

Improving benefit packages

There are many perks that employees would love to have with their salary package, but many organizations don’t realize this. However, organizations can take a cue from insurance companies by gathering health information about their staff and prospective candidates to provide them with a good health package or benefit.

According to a custom paper writing service, this is one way to remain attractive to both your staff and prospects in the market. However, transparency is a critical factor with issues like this so that you don’t have to face the legal problems arising from discrimination practices. You can do this by openly revealing how you get the data and how you are using it.

Dealing with legal and ethical issues

When it comes to big data, one thing that you can never take away from it is privacy. It is a big concern, and rightly so. There’s a legitimate fear in people about the possibility of using those numbers against them, which is described as being discriminatory. The use of big data for the Human Resource department has to be considered a technique for risk management.


There are many ways that HR can use big data. The truth is big data is useful in many parts of an organization, and the HR department isn’t left out. The advantages they stand to gain and the roles that it could play far outweigh whatever possible downside that might be there to it. So, it is worth looking into for organizations that don’t already take advantage of it. Some of its most significant benefits are described in this article.

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Podcast: Renee Troughton on Deep Introspection, Integrated Organisations and Looking Beyond Agile

MMS Founder
MMS Renee Troughton

Article originally posted on InfoQ. Visit InfoQ

00:21 Introductions

00:21 Shane Hastie: Good day folks. This is Shane Hastie for the InfoQ Engineering Culture Podcast. I’m at Agile Christchurch 2020, and I’m sitting down with Renee Troughton. Renee welcome. Thanks for taking the time to talk to us today.

00:34 Renee Troughton: Thanks for having me, Shane. It’s always awesome to talk to you.

00:37 Shane Hastie: Wonderful. It’s been a while since we’ve caught up. You and I obviously know each other well, I suspect some of my audience haven’t come across you on the Agile Revolution. So tell us a little bit about who you are and it’s introduce the Agile Revolution while we’re about it.

00:51 Renee Troughton: Awesome. So I’m an Enterprise Agile coach. I’m working for the Boston Consulting Group at the moment. I’ve been doing Agile for that 18 years now, and that’s transformations Agile, super love it. But I also love more the deeper things as well, the human connection, the softer side of Agile, but also the enterprise-based change where I sort of think about my role in life is bringing humanity back to business.

01:21 Shane Hastie: And what is the Agile Revolution?

01:22 Renee Troughton: Oh, the Agile Revolution is a thing. Yes, I should promote myself. So it’s podcasts that myself, Craig Smith and Tony Ponton run. We’ve been running it for a very long time. It feels like at least seven years. It’s got 140, I don’t know, plus, I’m going to get in trouble from Craig, episodes. But it ends up being both interviews that we’re doing much similar as now, but also our meanderings about the Agile space and the Agile world.

01:48 Shane Hastie: At this conference, you gave a talk Know Thyself Using Introspection to Coach Yourself. Why should I?

01:55 Renee Troughton: Why should you?

01:56 Shane Hastie: And what’s that about?

01:57 The value of introspection

01:59 Renee Troughton: Everyone should know how to coach themselves and how to think deeper about themselves because ultimately the ability to introspect effectively releases your soul, and it sounds very touchy feely, but it really releases the pain that you have inside of your life. So I would have categorized myself up until a few years ago as an extremely anxious person, both through elements of being bullied in the workplace, but also fears that I had of self-worth, even things around imposter syndrome as well. And I feel like through a few simple techniques, I’ve significantly been able to conquer a lot of those fears and through those techniques also have greater relationships, not just at work and with teams and in coaching conversations, but also at home. So, I’ve had a lot better of a relationship with my children, with my partner, as a result of these techniques.

02:45 Shane Hastie: What are some of the techniques? What do I do? Stand in front of a mirror and say, “Hi Shane,”?

02:50 Techniques for introspection

02:50 Renee Troughton: So it’s not mindfulness or meditation. So you’re not just there zenning away by yourself. I talk about three key techniques. So one of which most people in the Agile community aware of which is Christopher Avery’s responsibility process. The second of which maybe a few people in the Agile community aware of, which is nonviolent communication by Marshall Rosenberg and the third of which is Loving What Is the work that is done by Byron Katie. And so I utilize all three of these together to think about the conversations as they’re happening and to make better judgment in the way in which I respond in conversations. I didn’t necessarily learn them at the same time. I learned NVC first then the responsibility process then Loving What Is, but to go through them.

03:40 The responsibility process

03:40 Renee Troughton: And as an example, I mean the responsibility process is like a ladder. And it’s like a self-diagnosis of words you can use that sort of represent the state of mind that you’re in as you actually go through a conversation. So, I don’t use these every single moment of my life, but they’re very useful when you detect tension or things going awry. And so, whether that be tension amongst two individuals or tension in a team or in a coaching conversation you’re having, the responsibility process is sort of this ladder which you can meander around, but the ultimate goal is to get to ultimate responsibility. Now you could start in denial where you don’t believe it’s true. You could lay blame on others. You could justify the system that you’re in. You could shame yourself and say, “Yeah, I finally acknowledge it’s my fault.” Then just continue to beat yourself over where you could potentially quit. Then go up to obligation and obligation is where a lot of people work from, “No, it’s my job. I have to do it.” But true responsibilities is, “It’s my job. I love to do it.”

04:46 Renee Troughton: So knowing from an introspection perspective when you’re thinking about things, what state am I working from and is it truly responsibility and working yourself up through that particular process.

04:56 Non-violent communication

04:56 Renee Troughton: In nonviolent communication, it’s a technique that’s predominantly used as individuals communicate with each other, but it can also be self-used as well. The nonviolent communication is a very simple framework around the different types of language that we use being draft, being more open of the heart, language of love, respect, and deepness and jackal language being language that’s very much should, coulds, justs, which are effectively shame, lay blame and obligations that we’re placing on others. So the choices of the language that we make to do that.

05:49 Renee Troughton: In nonviolent communication it talks about this really simple syntax, which is thinking about responding to a situation using, what was the observed elements? So what actually happened factually in a particular event? How did you feel in that? What unmet needs weren’t being made in that event? And then a request for action. So would you be willing to change blah, blah, blah? But what I find interesting about nonviolent communication is this request element. We commonly ask of others to change. We don’t ask ourselves to change. And so, what I do is I apply introspection using this technique to change myself and ask myself to change.

06:33 Renee Troughton: So the example that I gave is a situation where I did get bullied at work. And any time that I got given this email saying, “Feedback,” as an example, “I’m going to give you feedback in four days time.” And the email triggered this memory whenever I see them. And occasionally I get feedback from managers to be fair, almost always it’s good feedback, but because I had such a huge event in my life where I was quite heavily bullied by feedback, anytime I get that and there’s a delay, for those next four days or whatever it is I’m just stewing. I cannot think about anything else in those moments.

07:11 Renee Troughton: And I used to handle it through a request to my manager to say, I gave him a bit of background about what happened, but also the request for them to be more timely in their feedback, or to caution it with some nice things as well. But it was always something that always triggered me when I ever received the word feedback. And if I apply NVC to myself, I think ultimately it went away as a pain point because what I realized was I wasn’t willing to let myself fail. And when I accepted that failure actually was an option, then it no longer became an issue.

07:48 Loving What Is

07:48 Renee Troughton: And so the last of the techniques is by Byron Katie around the work and it’s just is some really simple challenges to how you’re thinking about things. Is it true? The assumptions that you’re making, we talk about assumptions in lean startup and how things are hypotheses. Almost everything that goes in our head is a hypothesis. They should be better. These judgments are hypotheses that we force on others. And so if you think about this perspective of someone should be a better leader as an example, well, is it true? How can you really know it’s true? I don’t see them as a leader 100% of the time in everything that they possibly do. So I’m making a judgment call based upon a small amount of information. And so there’s been instances in the past where I’ve had, I would say, disconnected relationships with people. People that are just didn’t get on well with. It felt wrong. I don’t know really what was wrong. I don’t know what I did, what the interpretation was, but I couldn’t really fathom what happened with the interaction between me and that individual.

08:50 Renee Troughton: And since learning this I’ve challenged those assumptions. So I am now more proactive in going up to someone and going, “Look, I’ve sensed this. I’m really not quite sure what’s going on here.” And I’ll have that conversation. And every single time I’ve done it, the response has been amazing. It’s been, “Yeah, I sense there’s something weird too, but I didn’t know what it was either.” It’s always these assumptions that we’re making. And so by opening it up and truly introspecting as to whether it’s true or not, it gives you the freedom to say, “Can I test and learn if it’s right or not?” And then if it is still right, how do you feel in that moment? What are you giving up in yourself by continually thinking about that particular tension? And we live stewing in ourselves all the time because we just can’t get rid of these tensions that we really should just give up because it’s not doing us any good. And so there’s some extra few steps about turning it around and making it a joyous repositioning, but it’s really about challenging the self-denial that we live in every single day.

09:51 Shane Hastie: Not easy.

09:52 Renee Troughton: No, incredibly hard, but don’t beat yourself up. Just start trying. So keep going, like Agile, it’s an adaptive pattern you learn. You can just keep going. And eventually it’ll become second nature. I still fall down. There’s still occasions where I don’t do it right, where I still jump to judgment, but it’s less frequent. It’s less intense and I move out of it a lot faster.

10:15 Shane Hastie: So that’s self-awareness and self-management. Isn’t there something about emotional intelligence in there?

10:22 Renee Troughton: Probably. I mean, I’m a believer that emotional intelligence is something that you can grow in individuals. And these are just techniques to help you grow that.

10:31 Shane Hastie: Thank you for that. Other things that you’re engaged with and doing at the moment, you mentioned the idea about integrated organizations.

10:40 Ideas around integrated organisations

10:40 Renee Troughton: Yeah. I’m having this set of thoughts. Obviously, we’ve got movements towards Agile and organizations in business agility. We’ve got organizations that are starting down Teal path, which is more wholesome, self-management sort of environments. I think that the more successful transformations that I’ve ever seen, there’s some real clear denominators to it. And to be fair, it’s not because of Agile or it’s not because of Teal or anything else. Where I see it really successful is things, principles like flow efficiency, where people have optimized for getting outcomes, not output, to customers. Now I know that the essence of Agile is about all of this, but amongst all the processes out there, there’s sort of, we seem to have dissolved away from the original intent, but integrated organizations to me is about moving away from silos as one step. So integrating the value chain together, down to a team level to be able to deliver efficiently and effectively without handoffs.

11:43 Renee Troughton: So there’s movement towards no handoffs through integration. I think it’s also, there’s an element in there around multidisciplinary teams. Now we talk about it all the time in Agile, “We should just have multidisciplinary teams,” which is taking all these different specializations together and being able to deliver as one team. I’m a huge believer in polymaths or multidisciplinary individuals. So when I have personally felt that I’m given my most, that I’ve been my most successful, it’s in moments where my whole self is being fully utilized in all the different skills and talents that I have. I am not just an Agile person, for example. I do drawings and videos. I do podcasts. There’s many different skills that I bring to the table along with technology and even leadership elements, but very few organizations think about deep specializations in multiple points in individuals because they struggle just to get a team full of specialists together as a multidisciplinary team.

12:47 Renee Troughton: I think there’s this growing appreciation of deepening skill sets to have really adaptive organizations. So when you’ve got a team that can do each other’s jobs really effectively, without any diminishing returns, it really unlocks capacity and demand management inside of an organization as well.

13:06 Integrating self – being true to yourself irrespective of the context 

13:06 Renee Troughton: And then there’s this concept around integrating self. So we’ve talked about introspection, but often when I talk to individuals, they talk about their personality at work and their personality in their home life. And they’re different people. I think high-performance organizations are derived from people who actually have integrated both parts of themselves together. And I don’t mean necessarily skill sets or anything like that. What I mean is the person and how you behave with your families, the same person and how you behave with people at work, to bring your whole self to work. And then lastly, you get things like support services. So, why have HR and finance disconnected with the customer? How can you integrate customer back into how you’re delivering and integrate those support services back into how you’re delivering as well? So that there’s no one step away from the customer that often exists inside of organizations.

14:00 Shane Hastie: You’re talking to my soul here, #NoProjects. How many organizations are getting this right?

14:08 Why very few organisations are achieving integration

14:08 Renee Troughton: Very few, because I think they’re going on the Agile bandwagon because they see that’s the thing that’s out there, but I don’t think there’s real clarity to be fair out there about what scientifically works and what doesn’t work. And really only now we’re starting to detect a lot of those at scale patterns. There’s no dissent: amongst a team, agile is great to improve productivity and effectiveness and quality and speed to market. But I think it’s really struggling at scale because I don’t think we’ve actually scientifically nailed the principles that work and that don’t.

14:40 Shane Hastie: So how do we get there?

14:41 Renee Troughton: Well, like any scientific experiment, we should have clear hypothesis. We should have data and we should test and learn what works and what doesn’t work. I think, we tend in Agile to not do enough of that scientific based evaluation about what works and what doesn’t work. If you look at leadership as an example, there’s plenty of content out there about what works and what doesn’t work, but not a lot of is utilized because there’s so much other content out there.So there’s this diffusion that happens in leadership. If you look at performance and rewards. So we know already that incentivization for extrinsic based motivation, like performance bonuses for example, it just doesn’t work. Then why is 90% of the world still, or corporate world here, still use performance-based incentives and don’t pivot towards intrinsic? It’s because even if you do have the science, getting the message out there is challenging when there’s so much other dissent. So I think even if we do get to that science place, we’ve got to solve the problem of getting rid of the things that don’t work.

15:43 Shane Hastie: Easier said than done.

15:46 Renee Troughton: Yeah.

15:46 Shane Hastie: One other thing I’d like to explore, because you made a significant change. It’s about a couple of years ago now?

15:53 Renee Troughton: Yeah.

15:54 Shane Hastie: That’s-

15:54 Renee Troughton: Shocked a few people.

15:55 Shane Hastie: Shocked a lot of people.

15:58 Renee Troughton: Yeah.

15:59 Shane Hastie: You went to the dark side-

16:00 Renee Troughton: I went to the dark side.

16:01 Shane Hastie: … what was-

16:02 Renee Troughton: It’s the easiest way to say it. Yeah. So I joined a top tier consulting firm a few years ago after being an independent coach, effectively a boutique, for about 16 years.

16:12 Shane Hastie: It’s interesting in the Agile community and in the broader community looking from the outside at those organizations, they’re the ones we all love to hate.

16:21 Renee Troughton: Yeah, definitely.

16:23 Shane Hastie: So what’s it like being inside and what is the difference and perhaps a little bit of why?

16:28 Joining a top-tier consulting firm

16:28 Renee Troughton: Yeah, I think the why is a fairly simple story, in essence I was working at one bank in Australia at the time, and I was really starting to make some inroads. I’ve got all the coaches on board. We had an agreement of a way of working. We had co-created that with everyone inside of the organization. So there was a really strong momentum for change going forward, and everyone was super happy about moving forward with it. And then I was told by mid-level manager, “Sorry, but we’re going to go with a consulting company now.” And I don’t know what happened. I said, “Was it something I did or?” The whole feedback triggering sort of thing. And the response was, “No, it was just a decision that was made up on high.” And so I really struggled to get beyond a certain point.

17:11 Renee Troughton: There was a ceiling when I was in engagements that I would always hit as a coach, but also there was a curiosity, am I not good enough to speak to those people? Do I not know the right language to use? Do I not understand them enough? Why do these consultants, how do they get these gigs? And there was also a real fear at the same time. What do these consultants even know about Agile? I’ve been doing it a very long time, to what extent do they actually know anything? And I saw this potential future, which to be honest, I actually see playing out in Australia right now, where Agile gets a bad rep because it’s not being done properly or it ends up being just squads and chapters, as someone said today, which I think is partially true. I think to some extent consultancies tend to focus on surface level Agile.

18:07 Renee Troughton: And when you sort of dig underneath it, it’s probably not as much depth as you would hope to have. And rather than making these assumptions as to these hypotheses, and rather than continuing to not be able to break through that barrier, it was a bit of a, if you can’t beat them join them, but also help to influence from within so that when they were doing engagements, make sure that they know what real Agile actually looks like. That it’s co-created with clients. That it’s not just squads and chapters and that as much as possible trying to bring humanity back into that effort. So it’s not structure and org change, that it’s real values and leadership change associated with it. So that’s why I joined. And I didn’t end up joining the same consultant team that was brought in because I swiftly worked out that they actually did know nothing about Agile. And I wanted to make sure that I made a difference somewhere where I could believe in it.

18:59 Shane Hastie: So what’s it like working inside one of those big consultancies?

19:03 Working inside a top-tier consulting firm

19:03 Renee Troughton: A hypothesis that I had are not entirely all proven. I think to the point earlier, there was a little bit of surface level Agile, but I feel like consultancies are catching up really fast on the depth and the breadth and getting that content in there. How they interact with senior level execs and how they get into that position, we as an Agile community will never be able to touch. So, they build relationships that last decades, and they even have incentivization programs where when you leave the consultancy, you then go into a senior level position in an organization. Then you bring the consultancy back in. So, it’s like a racket system effectively. And so that’s why we would always struggle to get that level of engagement with senior level executives.

19:49 Renee Troughton: I think there’s the belief system in there that they’re all action, they don’t really care about the real outcome, that they don’t care about their own people. And I don’t really feel either of those is very true or certainly not in the case of BCG. There’s a real genuineness about the intent of the outcome, we’re there for helping clients to reach a specific outcome. But also, I really feel like in particular with BCG, I really feel part of a family. I feel like they do genuinely care, and they do genuinely listen to me as an Agile expert. So, I feel very respected from them, which is not what a lot of people would have thought from the outside looking in.

20:30 Renee Troughton: There’s an interesting exploration around what is the potential future of Agile. So if you think about the eras that we’ve sort of gone through, Agile has crossed the chasm now. It’s not just a software thing, which is a great thing. Now we’ve gotten everything we ever dreamed of as a community and what are we doing about it? So I feel like there’s this interesting potential futures going forward where potentially we could work better as a partnership, as both boutiques and consultancies together. I think there’s also an avenue where maybe boutiques ended up being just a small portion of transformations and all the consultancies get the larger ones, but there’s also, we’re already seeing a shift and I’m sure that you’ve heard about it as well, where there’s this shift away from Agile.

21:19 Shane Hastie: Certainly, Agile as a brand.

21:20 Renee Troughton: Yeah.

21:21 Shane Hastie: It’s kind of done its dash.

21:24 Looking at the future of agile in organisations

21:24 Renee Troughton: It’s done as dash, but I wouldn’t say there’s anything to replace it yet. And maybe that’s fair because to the point earlier, we haven’t done enough work to scientifically prove at scale and to educate at scale. I don’t think that Teal is actually going to be the next thing. I think there’s not enough proof behind that at all. And to be fair, it’s a whole stage of evolution different again. And we’re still in that struggling process between silo, command and control organizations to more collaborative based organizations. So I’m really pensive about what the future is. I agree that it’s probably not the Agile word, but we’ve got no clear thing coming up.

22:08 Shane Hastie: Is that a bad thing?

22:10 Renee Troughton: I think there’s something really powerful when you experienced Agile right in a team or even right in a department. And I’ve been really fortunate to be part of that when it’s worked really well at it a 700-person transformation. It was so dramatically different from a performance perspective from anywhere else, like four times difference in speed. Engagement wise, completely different. So double the amount of engagement, and cost-wise it was half the price despite competitors offshoring. So, I’m talking about like for like parity in feature delivery from one organization to another. So, I still think it has a place, yeah, but it’s hard to get it done right. And I think that’s where we don’t have consistency of patterns and where maybe through the commoditization of the Agile coaching environment, we don’t have enough real skills to actually get people there.

23:05 Shane Hastie: Renee, if people want to continue the conversation, where do they find you?

23:09 Renee Troughton: They can find me at or on LinkedIn via AgileRenee.

23:15 Shane Hastie: Thanks so much for taking the time to talk to us.

23:17 Renee Troughton: Thank you.

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Article: The Brain Is Neither a Neural Network nor a Computer: Book Review The Biological Mind

MMS Founder
MMS Michael Stiefel

Article originally posted on InfoQ. Visit InfoQ

Underlying much of artificial intelligence research is the idea that the essence of an individual resides in the brain. This is contrary to neuroscience which has discovered that a brain cannot work independently from the body and its environment. Understanding this enables us see what is reasonable to expect from artificial intelligence, as well as technology designed to improve human life.

By Michael Stiefel

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How big is the smart learning industry and how it will look like in the next 5 years?

MMS Founder

Article originally posted on Data Science Central. Visit Data Science Central

According to global smart learning Industry analysis by Research Dive, the global industry forecast will be $74,179.1 million in 2026, at a 19.2% CAGR and is growing from $18,200.0 million in2018.

Smart Learning industry Drivers: Growing acceptance of e-learning in academic & corporate sectors along with technological improvements in smart education is the major driver for the global smart learning growth. In addition, smart learning has observed a growth in its adoption due to several benefits including convenience and improved focus of learners. Moreover, it has empowered both students and teachers to enhance their efficiency and productivity. These abovementioned factors will boost the global growth in the projected time. In addition, growing trend of emergence of bring your own devices (BYOD) is estimated to rise the implementation of smart education and learning platforms, creating growth opportunities in the global. Furthermore, growing number of virtual schools across the globe is also further estimated to fuel the industry growth in the coming years. However, heavy investments are needed for implementation of advanced teaching technologies, which is a major restraining factor for the growth of the smart learning.

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Software component segment registered the highest global smart learning industry share in 2018; it was valued at $7,898.8 million and is projected to generate a revenue of $33,009.7 million till 2026. Software based online platforms provide digital classrooms with enabled virtual reality, and this software is widely being used in smart schools and emerging educational institutions. This factor is projected to drive the smart learning global growth in the coming years. Services component segment will garner up to $19,286.6 million in 2026 and is anticipated to grow at a health rate of 19.4% CAGR during the forecast timeframe.

TOP key Manufacturers:

The major smart learning players include SMART Technologies ULC, IBM, Saba Software, Huawei Technologies Co., Ltd, Cornerstone, McGraw-Hill, Alphabet, SAP, Blackboard Inc., Adobe, SAMSUNG, Oracle, BenQ, Microsoft, CrossKnowledge and Pearson. 

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Confluent Announces Strategic Alliance with Microsoft

MMS Founder
MMS Steef-Jan Wiggers

Article originally posted on InfoQ. Visit InfoQ

Confluent, the company of the founders of Apache Kafka, recently announced a new strategic alliance between them and Microsoft to enable a more integrated experience between Confluent Cloud and the Azure platform.

With Confluent Cloud as part of the Azure platform, customers can leverage Kafka as a managed service and stream data into Azure data services for low-latency, real-time analytics with pre-built connectors to Azure Data Lake Gen 2, Databricks, Cosmos DB, and Azure Synapse for analytics. Furthermore, they can create a fabric for event streams that span on-premises and cloud environments to enable modern cloud workloads to connect up to legacy systems – and leverage machine learning capabilities to get real-time insights from incoming data and share those insights with applications.


Confluent launched its fully-managed Apache Kafka service called Confluent Cloud a year ago on the Google Cloud Platform (GCP) marketplace first, followed by the Azure marketplace in March. Moreover, later the company also made Confluent Cloud available on the AWS marketplace. 

With the new alliance, the company strengthens its collaboration with Microsoft around the Confluent Cloud offering on Azure. Dan Rosanova, head of product management at Confluent Cloud, told InfoQ:

We had a marketplace integration before, but this partnership goes further; we now have integrated authentication based on AAD, so you get SSO out of the box. We supported SSO early, but it was a manual setup process, so you have two different identity chains, at least until you configured SSO. You also get to see your Confluent Cloud resources within the Azure portal and click right into our cloud experience right from Azure’s carrying that identity over without a separate login.

Customers can provision Confluent Cloud resources using Azure client interfaces like Azure portal, command-line interface (CLI), and software development kits (SDK)s. Furthermore, next to the SSO integration using Azure Active Directory, the service billing is unified through Azure.

Also, Rosanova said:

We do have other work coming, really continuing this integration and better serving our joint customers. We also partner with other cloud providers, but their cloud platforms aren’t the same. Our integrations and partnerships with them progress depend on many technical and business factors. Ideally, we want to make using Confluent Cloud as transparent and straightforward to customers of any cloud.

Confluent Cloud is available in the Azure marketplace, and customers can try it for free. Furthermore, details creating solutions through the Azure Marketplace are available in the Pay-As-You-Go Confluent Documentation and Commitments – Confluent Documentation.

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