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IBM releases Qiskit modules that use quantum computers to improve machine learning

April 11, 2021 Big Data

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IBM is releasing Qiskit Machine Learning, a set of new application modules that’s part of its open source quantum software. The new feature is the latest expansion of the company’s broader effort to get more developers to begin experimenting with quantum computers.

According to a blog post by the Qiskit Applications Team, the machine learning modules promise to help optimize machine learning by using quantum computers for some parts of the process.

“Quantum computation offers another potential avenue to increase the power of machine learning models, and the corresponding literature is growing at an incredible pace,” the team wrote. “Quantum machine learning (QML) proposes new types of models that leverage quantum computers’ unique capabilities to, for example, work in exponentially higher-dimensional feature spaces to improve the accuracy of models.”

Rather than replacing current computer architectures, IBM is betting that quantum computers will gain traction in the coming years by taking on very specific tasks that are offloaded from a classic computing system to a quantum platform. AI and machine learning are among the areas where IBM has said it’s hopeful that quantum can make an impact.

To make quantum more accessible, last year IBM introduced an open source quantum programming framework called Qiskit. The company has said it has the potential to speed up some applications by 100 times.

In the case of machine learning, the hope is that a system that offloads tasks to a quantum system could accelerate the training time. However, challenges remain, such as how to get large data sets in and out of the quantum machine without adding time that would cancel out any gains by the quantum calculations.

Developers who use Qiskit to improve their algorithms will have access to test them on IBM’s cloud-based quantum computing platform.

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Improve Work Breakdown Structure, Revenue Recognition, Resource Scheduling with Microsoft Dynamics 365 Project Operations

April 4, 2021 Microsoft Dynamics CRM

Project Management is the ultimate juggling act. There are always moving parts, several people involved, complicated project details, and critical accounting to track at every phase of the project at hand. It’s one thing to handle those details in typical checklist fashion and an entirely different scenario when leveraging a robust tool within Microsoft Dynamics 365. Microsoft Dynamics 365 Project…

Source

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PowerObjects- Bringing Focus to Dynamics CRM

Free Training – How to Leverage Sales Intelligence to Improve Sales Performance

March 10, 2021 CRM News and Info

Join us for this free training session and learn how to leverage sales intelligence technology to improve sales performance.

Date: March 18th
Time: 12-1pm Eastern

Research has proven that incorporating sales intelligence in your sales process significantly improves sales performance for B2B sellers. Harvard Business Review found that top-performing sales teams cite intelligence as a key driver fueling sales growth:

41% improvement in targeting
40% improvement in forecasting
34% improvement in lead quality
27% reduction in time spent looking for data
20% improvement in won opportunities
Be our guest for an informative session and learn how to incorporate sales intelligence into your sales cycle.

During this session you will learn:

What is sales intelligence?
The cost of missing & bad data to sales
How to uncover deep information about your prospects & customers
- Annual Revenue, ownership, employee count, and more
- Key contacts with verified email and telephone
- Technologies in use
- Industry info. and similar companies
Automatically update prospect & customer info
Day-in-the-life of sales using intelligence

All Attendees will receive 30 days of access to InsideView Insights, a leading B2B sales intelligence platform

CLICK HERE to register

About the Author: David Buggy is a veteran of the CRM industry with 18 years of experience helping businesses transform by leveraging Customer Relationship Management technology. He has over 17 years of experience with Microsoft Dynamics CRM/365 and has helped hundreds of businesses plan, implement and support CRM initiatives. To reach David or call 844.8.STRAVA (844.878.7282) To learn more about Strava Technology Group visit www.stravatechgroup.com

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CRM Software Blog | Dynamics 365

How Microsoft Azure DevOps and Dynamics 365 CRM Work Together to Improve Service Responsiveness

February 24, 2021 Microsoft Dynamics CRM

An upset customer calls. My system is down! This feature doesn’t work! While many issues are open and closed cases (or are the result of user error), there may be bugs that need to be addressed by the development team. Having a centralized place for your customer information is just one CRM function. Your CRM can also reduce inefficiencies in application support and management, especially when effectively connected to other systems. Integrating applications such as Microsoft Dynamics 365 CRM with Azure DevOps services amplifies case management capabilities for your development and support teams to escalate support cases and create work items to get problems resolved faster.

Outside of tech support’s ability to keep their cool when faced with high-stress situations, they must also act quickly. The more complicated the process and more systems involved, the longer it takes to get the ticket assigned to the right person or team. To help meet troubleshooting service goals, you need an open flow of communication right back to the source — the software development team.

Azure DevOps covers every step in the application lifecycle from planning, collaborating and testing, deployment, and beyond. If your business develops and/or hosts web or mobile apps, Azure DevOps services, integrated with Dynamics 365 CRM, can provide the full visibility across projects that your software development and tech support teams need.

Azure DevOps Services

Azure is a flexible public cloud computing platform that provides Infrastructure as a Service (IaaS), Platform as a Service (PaaS) and Software as a Service (SaaS). Continuous delivery (CD) and continuous integration (CI) pipelines enable your software development teams to get a constant flow of updates — new features, configurations, bug fixes — into production and delivered to your customers quickly and safely.

Microsoft Azure DevOps services allow you to build, test, deploy and manage applications and services. Your software development teams can use all these DevOps services together, or mix and match to use only what you need as part of your existing workflows.

Depositphotos 120503924 xl 2015 625x417 How Microsoft Azure DevOps and Dynamics 365 CRM Work Together to Improve Service Responsiveness — Business meeting between four upper management board members in the new modern office conference room with technology integrated in the form of an electronic tablet.

Azure Boards: Agile tools, Kanban boards, team dashboards, built-in scrum boards and more — Azure Boards is where your team will plan, track and discuss projects at every stage in the lifecycle. Backlog tracking and powerful analytics give insight into project status. With visualizations and tracking tools, your team can easily track any code changes that are linked directly to work items.

Azure Pipelines: Azure Pipelines comprise the whole end-to-end story of how you write code and get it into production. An integrated set of features allow you to automatically build and test your web, desktop and mobile applications and deploy to any cloud or on-premises. It works with just about any language or project type including Node.js, Python, Java, PHP, Ruby, C/C++, .NET, Android and iOS apps, as well as support for YAML so you can have pipelines versioned with your code.

Azure Test Plans: A browser-based test management solution, Azure Test Plans provides all the capabilities to test with confidence before deployment. This includes planned manual testing, user acceptance testing, exploratory testing, and gathering feedback from stakeholders. You can test across desktop and web apps, as well as capture data as tests are executed.

Azure Artifacts: Package management with Azure Artifacts simplifies complex build jobs and allows your teams to create and share Maven, npm, NuGet, and Python package feeds. Artifacts provide a place to push your packages so that they can be consumed by the rest of the team or partners. Sources can be public and private.

Azure Repos: This is where your source control is stored that gets published to the artifacts. Unlimited, cloud-hosted Git repos allow developers to collaborate on code.

Depositphotos 218890680 xl 2015 625x417 How Microsoft Azure DevOps and Dynamics 365 CRM Work Together to Improve Service Responsiveness — Working together in office. Business concept with double exposure effects

Before deploying Azure DevOps tools for your software development teams, it is wise to pre-plan how you will support and operate services in the cloud. To learn more about some of the key questions to ask before moving forward, read the full blog.

Get Started with JourneyTEAM

JourneyTEAM was recently awarded Microsoft US Partner of the Year for Dynamics 365 Customer Engagement (Media & Communications) and the Microsoft Eagle Crystal trophy as a top 5 partner for Dynamics 365 Business Central software implementations. Let JourneyTEAM show you the benefits of integrating Dynamics 365 and Azure DevOps Services. We can provide demos and full custom introductions. Contact JourneyTEAM today!

Article by: Dave Bollard – Chief Marketing Officer

801-436-6636

JourneyTEAM is an award-winning consulting firm with proven technology and measurable results. They take Microsoft products; Dynamics 365, SharePoint intranet, Office 365, Azure, CRM, GP, NAV, SL, AX, and modify them to work for you. The team has expert level, Microsoft Gold certified consultants that dive deep into the dynamics of your organization and solve complex issues. They have solutions for sales, marketing, productivity, collaboration, analytics, accounting, security and more. www.journeyteam.com

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CRM Software Blog | Dynamics 365

Facebook researchers propose ‘pre-finetuning’ to improve language model performance

February 2, 2021 Big Data

Machine learning researchers have achieved remarkable success with language model pretraining, which uses self-supervision, a training technique that doesn’t require labeled data. Pretraining refers to training a model with one task to help it recognize patterns that can be applied to a range of other tasks. In this way, pretraining imitates the way human beings process new knowledge. That is, using parameters of tasks that have been learned before, models learn to adapt to new and unfamiliar tasks.

For many natural language tasks, however, training examples for related problems exist. In an attempt to leverage these, researchers at Facebook propose “pre-finetuning,” a methodology of training language models that involves a learning step with over 4.8 million training examples performed on around 50 classification, summarization, question-answering, and commonsense reasoning datasets. They claim that pre-finetuning consistently improves performance for pretrained models while also significantly improving sample efficiency during fine-tuning.

It’s an approach that has been attempted before, often with success. In a 2019 study, researchers at the Allen Institute noticed that pre-finetuning a BERT model on a multiple choice question dataset appeared to teach the model something about multiple choice questions in general. A subsequent study found that pre-finetuning increased a model’s robustness for name swaps, where the names of different people were swapped in a sentence about which the model had to answer.

In order to ensure that their pre-finetuning stage incorporated general language representations, the researchers included tasks in four different domains: classification, commonsense reasoning, machine reading comprehension, and summarization. They call their pre-finetuned models MUPPET, which roughly stands for “Massive Multi-task Representation with Pre-finetuning.”

After pre-finetuning RoBERTa and BART, two popular pretrained models for natural language understanding, the researchers tested their performance on widely-used benchmarks including RTE, BoolQ, RACE, SQuAD, and MNLI. Interestingly, the results show that pre-finetuning can hurt performance when few tasks are used to a critical point, usually above 15 tasks. But pre-finetuning beyond this point leads to performance improvements correlated with the number of language tasks. MUPPET models outperform their vanilla pretrained counterparts and leveraging representations with 34-40 tasks enables the models to reach higher even accuracies with less data than a baseline RoBERTa model.

“These [performance] gains are particularly strong in the low resource regime, where there is relatively little labeled data for fine-tuning,” the researchers wrote in a paper describing their work. “We show that we can effectively learn more robust representations through multitask learning at scale. … Our work shows how even seemingly very different datasets, for example, summarization and extractive QA, can help each other by improving the model’s representations.”

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Kili Technology unveils data annotation platform to improve AI, raises $7 million

January 26, 2021 Big Data

Poor or uncategorized raw data can be a major impediment for enterprises that want to build high-quality artificial intelligence that has a meaningful impact on their business. Organizing unstructured data such as images and audio can present a particularly daunting obstacle in this regard.

Today, Paris-based Kili Technology unveiled its service that allows enterprises to annotate raw data such as video, drone aerial images, contracts, and emails. The company’s collaborative platform enables employees to make the data labeling process more efficient.

The company also said it had raised its first outside funding in a round led by Serena Capital and e.ventures, which invested along with business angels such as Datadog CEO Olivier Pomel, Algolia CEO Nicolas Dessaigne, and PeopleDoc founders Stanislas de Bentzmann and Gus Robertson. After a fast start, the company has ambitious plans to expand its international reach.

“The mission is super simple,” said Kili CEO and cofounder François-Xavier Leduc. “To build AI, you need three things. You need the computing power that you can buy easily on Amazon, you need an algorithm that is available as open source, and you need training sets. We are making the bridge between the raw data and what is required to build AI at scale for companies. Our mission is to help our customers turn this raw data into training data so that they can scale AI applications on their internal challenges to solve their issues.”

The company is part of a fast-moving and competitive data annotation sector. Dataloop last year raised $ 16 million for its data annotation tools. SuperAnnotate raised $ 3 million for its AI techniques that speed up data labeling. And earlier last year, IBM released annotation tools that tap AI to label images.

All of these companies have identified similar issues with developing high-quality AI: Getting data that can be readily processed to train AI. According to Kili, 29,000 Gigabytes of unstructured data are published every second, but much of it remains useless when it comes to training AI.

Founded in 2018 by Leduc and CTO Édouard d’Archimbaud, Kili offers a stable of experts to complement a company’s internal teams and help accelerate the annotation process.

Kili builds on work d’Archimbaud did while at BNP Paribas, where he ran the bank’s artificial intelligence lab. His team was trying to build models for processing unstructured data and ended up creating their own tools for data annotation.

Kili’s system, as d’Archimbaud explained, relies on a basic concept, similar to tagging people in a photo on Facebook. When users click on an image, a little box pops up so they can type in a name and attach a label to the image. Kili uses AI to allow enterprises to take this process to an industrialized scale to create higher-quality datasets.

“Before, people were thinking that AI was about algorithms, and having the most state-of-the-art algorithm,” d’Archimbaud said. “But it’s not the case anymore. Today, AI is about having the best data to train models.”

Kili’s cofounders bootstrapped the company for its first two years. But Kili has already attracted large customers in Europe, China, and the U.S. across a variety of industries.

As Kili gained more traction, the confounders decided to raise their first outside round of funding to accelerate sales and marketing. But they also intentionally sought out business angels who worked in other data-related startups to help provide practical guidance on building a global company to seize a growing opportunity.

“Two years ago, the data annotations market was estimated to be $ 2 billion in four years,” Leduc said. “And now it’s estimated to be $ 4 billion. It’s going to go fast, and it will definitely be huge. And it’s a new category. So there is an opportunity to be a worldwide leader. Today, we are positioned to be one of them.”

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Improve Your Accounting and Sales End-to-End Process with Dynamics 365 CRM and Dynamics 365 Business Central

December 8, 2020 CRM News and Info

Allied Modular Building Systems is a company that has provided specialized modular structures like high-tech robot enclosures, audio sound booths, and portable office spaces to some of the largest companies in the world. Recently, they’ve experienced rapid growth which their outdated and disconnected on-premise solutions couldn’t keep up. This resulted in downtime and a slow response to customer needs.

The company knew it needed to update its systems in order to create faster processes. With some Microsoft solutions already in place, they implemented Dynamics 365 and Business Central to bridge the gap between their additional business applications. Kevin Piethman, CEO, stated: “Dynamics 365 has been really powerful for us over the years. Our estimating and sales departments use the Sales app all the through to win or lose. When an order begins, we promote it over to Business Central. That integration is a huge time save because we don’t have to duplicate the information in two different places. All the sales data can flow with the order. We have saved about 19 percent of the cost per order by making this change–it’s one of the reasons we decided to implement this solution.”

With a simpler IT infrastructure and faster way to track customer information and opportunities, Allied Modular has created a seamless project flow, reduced IT costs, and connected teams.

Simplifying IT processes and creating a smoother flow is just one way hundreds of companies throughout the world are using Business Central and Dynamics 365 to improve end-to-end processes. Others have used the solution for more flexibility in managing data centers, to scale up or down, and to eliminate data silos.

Below, we’ll discuss what you can do with a Dynamics 365 and Business Central integration and how it will benefit your end-to-end processes.

Why Separate These Systems?

We at JourneyTEAM have been asked several times why Dynamics 365 CRM and Business Central are two separate systems rather than joined together.

Our answer is that these systems are separated, yet integrated. They work in conjunction with each other to provide organizations with detailed data, more flexibility, and a centralized marketing and sales planning and operations system. Small startups, acquisitions, or mergers can especially benefit from having two separate systems.

Let’s dive into this a little more.

Keeps Data Accurate Throughout the Entire Lifecycle

When you login to your marketing system to review data, you know that some of the data you’ve gathered is duplicate or incorrect. However, this isn’t cause for concern as this data will be verified and cleaned later on. Having false or duplicate data in your operating system is concerning because you make decisions based on the data stored here and you need it to be accurate. This is why it’s crucial to have all data verified before it reaches the accounting system. That way, when you login to your operating system, only real and precise vendor data is displayed, helping you to make faster, more educated decisions.

Flexibility

The cloud has enabled businesses to gather information from dozens of sources like eBay, Amazon, Shopify, WooCommerce, Magento, and more. Dynamics 365, a powerful CRM system, has the flexibility to gather that data from the different sources, identify similar data from each source, and feed it to the ERP.

Centralizes Marketing and Sales Planning and Operations

If you’re thinking that your sales inventory and operations planning systems are running just fine separately, you may be right. However, there are a number of benefits to centralizing these two systems. One of the biggest benefits is that your sales and marketing would work in tandem with each other.

A central SIOP system allows marketing and sales staff to identify opportunities and act on them from a single dashboard. For example, if your sales team has just completed a sale of several pieces of construction equipment. Your marketing team would be instantly alerted to this sale, giving them the chance to push service contracts, preventative plans, or other equipment. Not only does this help you increase profits, but also drives faster decisions.

Another benefit to a centralized SIOP is that your entire company would have access to this informative data. These insights can be accessed at any time, anywhere.

Finally, large complex businesses who want to mask the true complexity of their organization can do so with a centralized SIOP as customers would only see a single, seamless process.

Saves Time on Startup, Acquisition, or Merger Projects

Gone are the days where you had to go through the interruption of an ERP migration when you had a new startup, acquisition, or merger project. With Dynamics 365 and Business Central, you can use one of the existing connectors to integrate the two systems with ease.

Designed to Work for You

If you’ve read this information and thought: “I’m just a simple, low-volume startup–this all seems like overkill or isn’t for me”, think again. The best part about Dynamics 365 and Business Central is that they can be used in virtually any organization thanks to its flexible, agile tools.

We’ll take a closer look at each solution’s features and how they can benefit your end-to-end processes next.

Data Visualization

Both Business Central and Dynamics 365 feature a Power BI tool. This cloud-based reporting and analytics platform connects users to data stored throughout the organization through detailed reports and dashboards that provide deeper insight into various business teams and processes.

For example, if your business relies on a currency feed service, Power BI will aggregate all the data within your inventory and present it in an easy-to-read report or dashboard. You can even toggle between different views depending on what you’re looking for. Sales managers can look at how many items are stored at a specific warehouse location and inventory managers can ensure parts remain stocked or which locations are running low on certain items.

You can do all this and more from the ERP system, meaning you don’t have to build an integration between two systems.

Connect with Business Central

As soon as the connectors in Dynamics 365 are turned on, they begin working with your CRM system.

Once this integration is established, it goes to work aligning data in your inventory so you can view this data in an easy to read, simple way.

If you’re a smaller company or a startup, this low-volume, simple integration is a perfect introduction to Microsoft solutions. However, it’s important to note that if you’ve customized Business Central or your CRM system, this integration may be difficult or impossible as there’s little room for customization between the two systems.

File Export/Import Method

This is one of the most frequently used tools within Dynamics 365. Using this tool, you can import your master data from a CSV or Excel file and also use other features such as:

Include or exclude certain columns from the spreadsheet.
Automate tasks.
Customize fields for the source and target side.
Create sales invoices that feature headers and lines.

This tool is a great tool to use if you’re wanting to integrate with other tools. The import/export method allows you to first create the design for the field and table mapping before you export the data from the system into the spreadsheet. You can then drop this spreadsheet into Dynamics 365 and import the data.

Power Automate

As part of the Office 365 subscription, Dynamics 365 features the Power Automate tool. This tool allows users to create automated workflows between various systems to save time, reduce costs, gather data, receive notifications, and more. Power Automate can easily integrate with your favorite apps like other Microsoft Stack solutions, Dropbox, Trello, and popular social media sites like Instagram, Twitter, and Facebook.

The tool also allows you to:

Automate business processes or tasks
Send reminders about tasks.
Connect to hundreds of public APIs or data sources.
Reduce time spent on repetitive tasks.
Protect sensitive data.

For example, illimity, a cloud-native bank in Italy, used Power Automate to simplify, streamline, and automate a slow, inefficient approvals process. Today, the company has saved a significant amount of time in customer requests using the features within Power Automate.

Dynamics 365 API Integration

To help you gather data from each of your applications, use the direct API integration in Dynamics 365. Setting this integration takes very little time, but is harder and more expensive to maintain. However, the expense is definitely worth it thanks to the speed and efficiency that is unrivaled in Power Automate.

The Benefits of Microsoft

Why go with Microsoft and not with another system? There are hundreds of CRM and ERP systems to choose from, so what makes Microsoft the best? The answer is flexibility. Few other systems provide the flexibility and agility that Business Central and Dynamics 365 do. From small, low-volume startups to large, complex, high-volume businesses, these systems can be configured to support your unique business processes. Streamlined, efficient processes lead to better customer services, more targeted marketing, and more effective sales strategies.

In addition to these benefits, Dynamics 365 and Business Central can help you:

Gain deeper insight into customer data using powerful, versatile tools.
Increase business as both these systems work together to analyze data and find promising leads or sales opportunities.
Provide your entire organization with fast, easy access to valuable data insights by storing data in one place.
Improve both customer retention and satisfaction by helping your sales, marketing, or customer service team respond more quickly and appropriately to their needs.

Microsoft prides themselves on creating solutions that are designed to work for you, making the list of benefits endless. Implementing just one of these solutions can be the catalyst to implementing others, helping you to further advance and improve your business processes.

Enjoy Customized Support from a Microsoft Partner

When you need assistance with either Business Central or Dynamics 365, contact JourneyTEAM, a Microsoft Gold Partner. With the help of our talented team of professionals who are well-versed in Microsoft solutions, we’ll help you get these solutions up and running as quickly as possible. Whether you need a lot of support or a little, we’re happy to provide it. Talk to a JourneyTEAM representative today!

JourneyTEAM was recently awarded Microsoft US Partner of the Year for Dynamics 365 Customer Engagement (Media & Communications) and the Microsoft Eagle Crystal trophy as a top 5 partner for Dynamics 365 Business Central software implementations. Our team has a proven track record with successful Microsoft technology implementations and wants you to get the most out of your organization’s intranet system. Consolidating your communication, collaboration, and productivity platform with Microsoft will save time and money for your organization. Contact JourneyTEAM today!

Improve Your Accounting and Sales End to End Process with Dynamics 365 CRM and Dynamics 365 Business Central Article by: Dave Bollard – Chief Marketing Officer | 801-436-6636

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CRM Software Blog | Dynamics 365

IBM claims its AI can improve neonatal outcomes and predict the onset of Type 1 diabetes

November 20, 2020 Big Data

IBM this week presented research investigating how AI and machine learning could be used to improve maternal health in developing countries and predict the onset and progression of Type 1 diabetes. In a study funded by the Bill and Melinda Gates Foundation, IBM researchers built models to analyze demographic datasets from African countries, finding “data-supported” links between the number of years between pregnancies and the size of a woman’s social network with birth outcomes. In a separate work, another team from IBM analyzed data across three decades and four countries to attempt to anticipate the onset of Type 1 diabetes anywhere from 3 to 12 months before it’s typically diagnosed and then predict its progression. They claim one of the models accurately predicted progression 84% of the time.

Improving neonatal outcome

Despite a global decline in child mortality rates, many countries aren’t on track to achieving proposed targets of ending preventable deaths among newborns and children under the age of 5. Unsurprisingly, the progress toward these targets remains uneven, reflected in disparities in access to health care services and inequitable resource allocation.

Toward potential solutions, researchers at IBM attempted to identify features associated with neonatal mortality “as captured in nationally representative cross-sectional data.” They analyzed corpora from two recent (from 2014 and 2018) demographic and health surveys taken in 10 different sub-Saharan countries, building for each survey a model to classify (1) the mothers who reported a birth in the 5 years preceding the survey, (2) those who reported losing one or more children under the age of 28 days, and (3) those who didn’t report losing a child. Then, the researchers inspected each model by visualizing the features in the data that informed the model’s conclusions, as well as how changes in the features’ values might have impacted neonatal mortality.

The researchers concluded that that in most countries (e.g., Nigeria, Senegal, Tanzania, Zambia, South Africa, Kenya, Ghana, Ethiopia, the Democratic Republic of the Congo, and Burkina Faso), neonatal deaths accounts for the majority of the loss of children under 5 years and that the percentages of neonatal deaths have historically remained high despite a decrease in under-5 deaths. They found that the number of births in the past 5 years was positively correlated with neonatal mortality, while household size was negatively correlated with neonatal mortality. Furthermore, they claimed to have established that mothers living in smaller households have a higher risk of neonatal mortality compared to mothers living in larger households, with factors such as the age and gender of the head of the household appearing to influence the association between household size and neonatal mortality.

The coauthors of the study note the limitations of their work, like the fact that the surveys, which are self-reported, might omit key information like health care access and health care-seeking behaviors. They also concede that the models might be identifying and exploiting undesirable patterns to make their predictions. Still, they claim to have made an important contribution to the research community in demonstrating that ensemble machine learning can potentially derive neonatal outcome insights from health surveys alone.

“Our work demonstrates the practical application of machine learning for generating insights through the inspection of black box models, and the applicability of using machine learning techniques to generate novel insights and alternative hypotheses about phenomena captured in population-level health data,” the researchers wrote in a paper describing their efforts. “The positive correlation between the reported number of births and neonatal mortality reflected in our results confirms the previously known observation about birth spacing as a key determinant of neonatal mortality.”

Type 1 diabetes prediction

A separate IBM team sought to investigate the extent to which AI might be useful in diagnosing and treating Type 1 diabetes, which affects about 1 in 100 adults during their lifetimes. Drawing on research showing that clinical Type 1 diabetes is generally preceded by a condition called islet autoimmunity, in which the body consistently produces antibodies called islet autoantibodies, the team developed an algorithm that clusters patients together and determines the number of clusters and their profiles to discover commonalities across different geographical groups.

The algorithm considered profiles based on types of autoantibodies, the age at which autoantibodies were developed, and imbalances in autoantibody positivity. After clustering the autoantibodies-positive subjects together, the researchers applied the model to data from 1,507 patients across studies conducted in the U.S., Sweden, and Finland. The accuracy of cluster transfer was reportedly high, with a mean of the aforementioned 84%, suggesting that the AAb profile can be used to predict Type 1 diabetes progression independently of the population.

In a related study, this same team of researchers created a Type 1 diabetes ontology that captures the patterns of certain biomarkers and uses them together with a model to discern features. The coauthors claim that when applied to the same datasets as the clustering algorithm, the ontology improved prediction performance for up to 12 months in advance, enabling predictions of which patients might develop Type 1 diabetes a year before it’s usually detected.

It’s important to note, of course, that imbalances in the datasets might have biased the predictions. A team of U.K. scientists found that almost all eye disease datasets come from patients in North America, Europe, and China, meaning eye disease-diagnosing algorithms are less certain to work well for racial groups from underrepresented countries. In another study, Stanford University researchers claimed that most of the U.S. data for studies involving medical uses of AI come from California, New York, and Massachusetts.

The coauthors of an audit last month recommend that practitioners apply “rigorous” fairness analyses before deployment as one solution to bias. Here’s hoping that the IBM researchers, should they choose to eventually deploy its models, heed their advice.

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Big Data – VentureBeat

Why Digital Transformation Is Essential to Improve Business Outcomes

November 14, 2020 CRM News and Info

Peak commercial performance — it’s what all organizations strive to reach. At the most baseline level, we’re talking about sustained, profitable growth. But while talking about it seems easy enough, actually getting there is another story.

Businesses that have cracked the code adapted to meet the evolving needs of the customer in spite of the increasing complexity of an ever-changing economy.

Doing so successfully requires them to find ways to accelerate revenue and manage key relationships, while tackling the complexity that threatens to slow them down.

The Keys to Digital Transformation

If you look at who’s winning in the market, it’s the companies that not only embraced digital transformation early, but also made it a core building block of their foundation moving forward.

So, what does it take to win today? The most successful companies have five key things in common:

1. Analyzing top-down to know where to start a digital transformation journey.

Before a company can even think about the technology it is looking to implement, it must first analyze the business as a whole and the objectives it is trying to achieve.

It is important to fully understand “who” the company is today, and how it has changed over time or under the current circumstances. Once companies understand this, they are in a better position to reshape business architectures in a way that best aligns with business goals.

Another option is to work with a third-party vendor to perform an audit of the company. This will help to get an unbiased view on where a company can improve. A vendor would also be able to provide industry best practices on what similar businesses have done to become more efficient.

2. Securing buy-in from all teams, especially company leaders.

Cultural transformation is the key to digital transformation success. One of the biggest challenges companies face when implementing new digital strategies is ensuring all team members are on board. This can be done through strong and clear internal communication. Outlining clear key performance indicators that will help show benefits such as increased sales effectiveness, customer satisfaction, and revenue, will help everyone involved understand why changes must be made.

When company leaders are on board, they can help act as advocates for projects and initiatives, while encouraging and rewarding agility amongst the rest of the teams involved. It is also crucial to provide training on any new technologies prior to implementation, while continuing to support and tend to any questions, and troubleshooting as new strategies are being rolled out.

3. Meeting customers wherever they are in their digital transformation journey.

The popular adage ‘patience is a virtue’ doesn’t apply when achieving peak commercial performance is the end goal. Doing business gets harder every day because the ever-increasing complexities of a changing economy causes friction between companies and their customers.

Victory goes to those who are impatient and challenging the status quo with new business models that leverage digital transformation for speed. Those who can remove that friction are performing disproportionately well, even in the unpredictable times we are in today.

The secret to removing friction is meeting customers wherever they are in their digital transformation journey. This applies to businesses of all types across various industries — from small retailers trying to bridge the technological gap with their older buyers, to large manufacturers that want to simplify complex purchase and fulfillment processes.

Winning businesses are transforming the way customers do this by meeting them where they are on the journey and enabling them to provide an enjoyable and frictionless customer experience.

4. Making customers business-agile so they can move at the speed of their customers.

Another key component of digital transformation is the ability to move at the speed of the customer. Businesses that get it right invest in ways that will get the customer from Point A to Point B as quickly and painlessly as possible. This requires an understanding that it’s less about features and functions and more about removing screens, clicks, and other bottlenecks.

For example, consider Door Dash’s success over the past six months. While the food delivery service was doing well prior to COVID-19, it’s been doing even better during shelter-in-place and quarantine. Door Dash understood the points of friction in their customer’s journey and implemented things like touchless payment and contactless pickup.

Today, the volume of its pickup business is growing by double digits as a result of removing friction and enabling customers to pay for and receive their meals sooner. Success requires moving faster to meet customer needs today while simultaneously increasing agility to prepare for an uncertain tomorrow.

5. Providing customers with resources for an all-digital, work-from-anywhere world.

Remaining agile in a dynamic market requires the ability to go fast in a straight line while also navigating around corners with confidence. This is especially important as companies grow and dodge inevitable curve balls during their digital transformation efforts.

For example, today we must provide customers with the resources they need to succeed in an all-digital, work-from-anywhere world. Because let’s face it, even when the pandemic is under control, the return to the office will never look like what it used to. Businesses that invest in ways to help customers tackle complexity with confidence add capabilities under the hood to make features and functions faster, more dependable, and scalable.

Conclusion

High-performing businesses reach peak commercial performance by reducing friction in customer interactions in the face of a market with increasing complexity. Those who can meet their customers at any point on their digital transformation journey to help them move at the speed of their customers in an all-digital, work-from-anywhere world, are set up for success today and well into an uncertain tomorrow.

Eric%20Carrasquilla Why Digital Transformation Is Essential to Improve Business Outcomes
Eric Carrasquilla is SVP of Product at Conga, where he is responsible for the vision, design, and delivery of Conga product portfolio. Eric has over 20 years of experience building, launching, and monetizing enterprise grade applications that deliver successful customer experiences. Prior to Conga, Eric served as SVP of Product at Model N where he led the strategy to identify and drive the right angle to enter markets and dominate them with innovative products and solutions. He has also held various product and marketing leadership roles at [24]7.ai, Amdocs, Baan, and Fujitsu. Eric holds an MBA from Santa Clara University and a BS in Marketing from San Jose State University.

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Google details how it’s using AI and machine learning to improve search

October 16, 2020 Big Data

During a livestreamed event this afternoon, Google detailed the ways it’s applying AI and machine learning to improve the Google Search experience.

Soon, Google says users will be able to see how busy places are in Google Maps without having to search for specific beaches, parks, grocery stores, gas stations, laundromats, pharmacies, or other business, an expansion of Google’s existing busyness metrics. The company also says it’s adding COVID-19 safety information to business profiles across Search and Maps, revealing whether they’re using safety precautions like temperature checks, plexiglass, and more.

An algorithmic improvement to “Did you mean,” Google’s spell-checking feature for Search, will enable more accurate and precise spelling suggestions. Google says the new underlying language model contains 680 million parameters — the variables that determine each prediction — and runs in less than three milliseconds. “This single change makes a greater improvement to spelling than all of our improvements over the last five years,” Prabhakar Raghavan, head of Search at Google, said in a blog post.

Beyond this, Google says it can now index individual passages from webpages as opposed to whole pages. When this rolls out fully, it will improve roughly 7% of search queries across all languages, the company claims. A complementary AI component will help Search capture the nuances of what webpages are about, ostensibly leading to a wider range of results for search queries.

“We’ve applied neural nets to understand subtopics around an interest, which helps deliver a greater diversity of content when you search for something broad,” Raghavan continued. “As an example, if you search for ‘home exercise equipment,’ we can now understand relevant subtopics, such as budget equipment, premium picks, or small space ideas, and show a wider range of content for you on the search results page.”

Google is also bringing Data Commons, its open knowledge repository that combines data from public datasets (e.g., COVID-19 stats from the U.S. Centers for Disease Control and Prevention) using mapped common entities, to search results on the web and mobile. In the near future, users will be able to search for topics like “employment in Chicago” on Search to see information in context.

On the ecommerce and shopping front, Google says it has built cloud streaming technology that enables users to see products in augmented reality (AR). With cars from Volvo, Porsche, and other “top” auto brands, for example, they can zoom in to view the steering wheel and other details in a driveway, to scale, on their smartphones. Separately, Google Lens on the Google app or Chrome on Android (and soon iOS) will let shoppers discover similar products by tapping on elements like vintage denim, ruffle sleeves, and more.

Google details how it’s using AI and machine learning to improve search

Above: Augmented reality previews in Google Search.

Image Credit: Google

In another addition to Search, Google says it will deploy a feature that highlights notable points in videos — for example, a screenshot comparing different products or a key step in a recipe. (Google expects 10% of searches will use this technology by the end of 2020.) And Live View in Maps, a tool that taps AR to provide turn-by-turn walking directions, will enable users to quickly see information about restaurants including how busy they tend to get and their star ratings.

Lastly, Google says it will let users search for songs by simply humming or whistling melodies, initially in English on iOS and in more than 20 languages on Android. You will able to launch the feature by opening the latest version of the Google app or Search widget, tapping the mic icon, and saying “What’s this song?” or selecting the “Search a song” button, followed by at least 10 to 15 seconds of humming or whistling.

“After you’re finished humming, our machine learning algorithm helps identify potential song matches,” Google wrote in a blog post. “We’ll show you the most likely options based on the tune. Then you can select the best match and explore information on the song and artist, view any accompanying music videos or listen to the song on your favorite music app, find the lyrics, read analysis and even check out other recordings of the song when available.”

Google says that melodies hummed into Search are transformed by machine learning algorithms into a number-based sequence representing the song’s melody. The models are trained to identify songs based on a variety of sources, including humans singing, whistling, or humming, as well as studio recordings. They also take away all the other details, like accompanying instruments and the voice’s timbre and tone. This leaves a fingerprint that Google compares with thousands of songs from around the world and identify potential matches in real time, much like the Pixel’s Now Playing feature.

“From new technologies to new opportunities, I’m really excited about the future of search and all of the ways that it can help us make sense of the world,” Raghavan said.

Last month, Google announced it will begin showing quick facts related to photos in Google Images, enabled by AI. Starting in the U.S. in English, users who search for images on mobile might see information from Google’s Knowledge Graph — Google’s database of billions of facts — including people, places, or things germane to specific pictures.

Google also recently revealed it’s using AI and machine learning techniques to more quickly detect breaking news around crises like natural disasters. In a related development, Google said it launched an update using language models to improve the matching between news stories and available fact checks.

In 2019, Google peeled back the curtains on its efforts to solve query ambiguities with a technique called Bidirectional Encoder Representations from Transformers, or BERT for short. BERT, which emerged from the tech giant’s research on Transformers, forces models to consider the context of a word by looking at the words that come before and after it. According to Google, BERT helped Google Search better understand 10% of queries in the U.S. in English — particularly longer, more conversational searches where prepositions like “for” and “to” matter a lot to the meaning.

BERT is now used in every English search, Google says, and it’s deployed across languages including Spanish, Portuguese, Hindi, Arabic, and German.

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