Deloitte has acquired Brisbane-based data analytics and financial performance management specialist Bistech for an unspecified sum.

Bistech will join Deloitte’s data analytics team in Brisbane, with Bistech co-owners Shane Morgan, Justin Hoareau and Brad Culbert in leadership roles. All 17 consultants will also join Deloitte.

“We’re incredibly excited and pleased to be joining Deloitte’s Analytics & Cognitive team, which shares the same people values and customer focus we’ve built over the last 19 years in business,” Bistech founder Shane Morgan said in a statement.

Founded in 2000, Bistech provides data analytics, data science, data management and financial performance management services in the form of consulting, technical implementation, support and training.

Its vendor partners include Microsoft, IBM and Adaptive Insights.

The company was a two-time CRN Fast50 finalist in 2015 and 2016, and was also a finalist in the CRN Impact Awards for Evolving Innovator in 2018.

“The Bistech team bring a great mix of business and technical expertise that is increasingly in demand from clients seeking to extract maximum benefit from their data,” Deloitte Consulting managing partner Kaylene O’Brien said.

“Their service offerings closely align with client demand, including data architecture, cloud data solutions migration, data asset modernisation, predictive analytics and machine learning.”

The post Deloitte acquires Microsoft, IBM partner Bistech appeared first on Artificial Intelligence.

ClouDhiti today announces the launch of its AI Apps with the aim to empower online retailers, especially small and medium businesses (SMBs), with AI capabilities. With these five new apps, all available on the ClouDhiti Marketplace, SMBs don’t have to hire expensive technical developers or buy software that they don’t understand nor know how to operate.

Included in the five new AI Apps are two variations of AI Chatbots, one catered to general online stores and another to stores on the Shopify platform. The AI Chatbots are ready-embedded with cognitive and natural language understanding (NLU) capabilities to create a seamless and personal customer experience.

Customers are also able to get their hands on the Shopify Store AI Analytics App. This app analyzes product purchases, inventory data and customer transactions to provide AI-based actionable insights and recommendations to boost sales and craft marketing strategies.

In addition, two versions of the AI Anomaly Detection App are available for online and Shopify stores. By using anomaly detection in web server logs and Shopify store logs, these apps can identify potential threats and fraudulent activities and operational issues and alert the store owner accordingly with recommendations for possible next steps. 

In order to deploy any of the apps, customers only need to browse through ClouDhiti’s AI Apps Marketplace, select whichever apps meet their business needs, connect them to their datasets, and try them out, free of charge. Deployment is a simple matter of clicking one button, rather than the usual involvement of coding and/or IT teams.

With these AI apps, businesses can use AI technologies to serve their specific business needs by improved customer service, targeted marketing campaigns, or threat detection. AI Apps can scale according to customers’ exact requirements, and ClouDhiti’s seasoned team of data scientists and data engineers are there around the clock to support app deployment and usage. 

“I decided to employ the Syra AI Chatbot on our website to enhance the customer experience in a variety of ways, including answering questions about the menu, helping site visitors place orders, and to participate in our promotions,” said  Rick Richman Founder of Firepie, a high-speed pizza delivery food-tech concept in San Francisco. “This allows us not only to keep our customers engaged on our site but also to build meaningful relationships with them and keep them coming back.” 

ClouDhiti’s AI Apps are the ideal solution for SMBs that do not have the resources to invest in AI development, with their own efforts to create AI solutions often unable to guarantee a fast and direct ROI. However, that’s not to say that SMBs should hold off from introducing AI, especially as it’s now available in an off-the-shelf package form. In fact, according to research done by Salesforce, only 8% of SMBs are using AI today, but almost half of SMB leaders say they are ready to adopt the technology. 

Mike Habib, an IRS-licensed enrolled agent providing nationwide tax representation services, based in Los Angeles, is one of those leaders: “I decided to deploy the Syra AI Chatbot on my website to engage site visitors and generate leads,” he said. “I’m very excited to see the additional sales activity and improvement to customer relationships it brings.” 

“We are extremely excited to be able to offer SMBs the opportunity to leverage AI and its capabilities in ways that would be otherwise either be extremely costly or simply impossible for many of them,” said Aparajeeta Das, Founder and CEO at ClouDhiti. “With our five AI Apps, small businesses can have access to valuable insights and build customer relationships as if they are a large enterprise.”

ClouDhiti plans to add new apps every quarter. The apps are available in the ClouDhiti Marketplace today and other marketplaces like Shopify (for online retailers), Zendesk (for IT Support), and as a Plugin for WordPress based Stores.

The post ClouDhiti Launches AI Apps to Empower SMBs with AI appeared first on Artificial Intelligence.

BHUBANESWAR:  Technical students in Odisha will soon have the opportunity to get training on Artificial Intelligence (AI) to develop smart machines.

Skill Development and Technical Education Minister Premananda Nayak said a Centre of Excellence has been set up by Tech Mahindra and Biju Patnaik University of Technology (BPUT) at the College of Engineering and Technology (CET) here where a 6 to 12-month course on AI technology will be provided to the students. 

The centre will also offer training to professionals to address the AI technology-related issues emerging in various government organisations and industries.

The Minister, who revealed this in a written reply to MLA Soumya Ranjan Patnaik in the Assembly, said steps have been taken to provide skill training to students on AI and coding. 

The training on AI would help students build smart machines capable of performing tasks that typically require human intelligence. As per the Survey of Aspiring Minds-2019, only 2.5 per cent engineers have expertise in AI while 4.6 per cent have skills on coding in the State. 

To address the issue, the Minister said facility has been created for skill training on AI and Coding at CET and provisions have been made to provide extra coding courses such as Python, C and C++ to the students. Similarly, skill training on coding is being provided at engineering colleges and polytechnics through CISCO NetAcad programme. 

Nayak said Veer Surendra Sai University of Technology (VSSUT), Burla has geared up to offer courses on AI and machine learning under TEQIP-III programme. Besides, supercomputers have been installed at VSSUT, CET, IGIT and Parala Maharaj College of Engineering with support from C-DAC for high-speed computing and machine learning, the Minister added.

The post Artificial Intelligence training for technical students in Odisha soon appeared first on Artificial Intelligence.

Trying to get a handle on the progress of artificial intelligence is a daunting task, even for those enmeshed in the AI community. But the latest edition of the AI Index report — an annual rundown of machine learning data points now in its third year — does a good job confirming what you probably already suspected: the AI world is booming in a range of metrics covering research, education, and technical achievements.

The AI Index covers a lot of ground — so much so that its creators, which include institutions like Harvard, Stanford, and OpenAI, have also released two new tools just to sift through the information they sourced from. One tool is for searching AI research papers and the other is for investigating country-level data on research and investment.

Most of the 2019 report basically confirms the continuation of trends we’ve highlighted in previous years. But to save you from having to trudge through its 290 pages, here are some of the more interesting and pertinent points:

• AI research is rocketing. Between 1998 and 2018, there’s been a 300 percent increase in the publication of peer-reviewed papers on AI. Attendance at conferences has also surged; the biggest, NeurIPS, is expecting 13,500 attendees this year, up 800 percent from 2012.
• AI education is equally popular. Enrollment in machine learning courses in universities and online continues to rise. Numbers are hard to summarize, but one good indicator is that AI is now the most popular specialization for computer science graduates in North America. Over 21 percent of CS PhDs choose to specialize in AI, which is more than double the second-most popular discipline: security / information assurance.
• The US is still the global leader in AI by most metrics. Although China publishes more AI papers than any other nation, work produced in the US has a greater impact, with US authors cited 40 percent more than the global average. The US also puts the most money into private AI investment (a shade under $12 billion compared to China in second place globally with $6.8 billion) and files many more AI patents than any other country (with three times more than the number two nation, Japan).
• AI algorithms are becoming faster and cheaper to train. Research means nothing unless it’s accessible, so this data point is particularly welcome. The AI Index team noted that the time needed to train a machine vision algorithm on a popular dataset (ImageNet) fell from around three hours in October 2017 to just 88 seconds in July 2019. Costs also fell, from thousands of dollars to double-digit figures.
• Self-driving cars received more private investment than any AI field. Just under 10 percent of global private investment went into autonomous vehicles, around $7.7 billion. That was followed by medical research and facial recognition (both attracting $4.7 billion), while the fastest-growing industrial AI fields were less flashy: robot process automation ($1 billion investment in 2018) and supply chain management (over $500 million).

All this is impressive, but one big caveat applies: no matter how fast AI improves, it’s never going to match the achievements accorded to it by pop culture and hyped headlines. This may seem pedantic or even obvious, but it’s worth remembering that, while the world of artificial intelligence is booming, AI itself is still limited in some important ways.

The best demonstration of this comes from a timeline of “human-level performance milestones” featured in the AI Index report; a history of moments when AI has matched or surpassed human-level expertise.

The timeline starts in the 1990s when programs first beat humans at checkers and chess, and accelerates with the recent machine learning boom, listing video games and board games where AI has came, saw, and conquered (Go in 2016, Dota 2 in 2018, etc.). This is mixed with miscellaneous tasks like human-level classification of skin cancer images in 2017 and in Chinese to English translation in 2018. (Many experts would take issue with that last achievement being included at all, and note that AI translation is still way behind humans.)

And while this list is impressive, it shouldn’t lead you to believe that AI superintelligence is nigh.

For a start, the majority of these milestones come from defeating humans in video games and board games — domains that, because of their clear rules and easy simulation, are particularly amenable to AI training. Such training usually relies on AI agents sinking many lifetimes’ worth of work into a single game, training hundreds of years in a solar day: a fact that highlights how quickly humans learn compared to computers.

Similarly, each achievements was set in a single domain. With very few exceptions, AI systems trained at one task can’t transfer what they’ve learned to another. A superhuman StarCraft II bot would lose to a five-year-old playing chess. And while an AI might be able to spot breast cancer tumors as accurately as an oncologist, it can’t do the same for lung cancer (let alone write a prescription or deliver a diagnosis). In other words: AI systems are single-use tools, not flexible intelligences that are stand-ins for humans.

But — and yes, there’s another but — that doesn’t mean AI isn’t incredibly useful. As this report shows, despite the limitations of machine learning, it continues to accelerate in terms of funding, interest, and technical achievements.

When thinking about AI limitations and promises, it’s good to remember the words of machine learning pioneer Andrew Ng: “If a typical person can do a mental task with less than one second of thought, we can probably automate it using AI either now or in the near future.” We’re just beginning to find out what happens when those seconds are added up.

The post AI R&D is booming, but general intelligence is still out of reach appeared first on Artificial Intelligence.

In a sign of the cloud market’s maturity, vendors are partnering to offer multi-tiered service integrations.

Vendor alliances, such as a Microsoft and Oracle partnership, could help enterprises with multi-cloud deployment models. If the partnership is successful, customers could glean greater power and flexibility for critical groups such as data analysts, application developers and enterprise architects.

The Oracle and Microsoft partnership means businesses can run part of a workload within Azure and another aspect of that workload within Oracle Cloud Infrastructure (OCI). In addition, IT teams can migrate workloads and data as needed between the environments, exploiting the strengths of each one.

The Microsoft and Oracle partnership is significant beyond cloud services, because both companies provide a diverse range of business applications.

See how Oracle and Microsoft’s dealings will affect your organization’s cloud features, support, security and technical integrations, as well as the potential use cases for these multi-cloud vendor connections.

Perks of the partnership

The Microsoft and Oracle partnership, which began in June 2019, benefits each company’s customer base, but in different ways. Microsoft Azure’s user base gets access to business-focused resources and well-known Oracle enterprise applications. For Oracle, Azure accessibility enhances existing products.

For example, IT teams can deploy the Oracle Autonomous Database, which is managed via machine learning rather than admins, with Microsoft’s AI, business intelligence and data analytics technologies. Oracle also offers its users a more comprehensive cloud infrastructure for compute and data storage through Azure than via Oracle Cloud alone.

With interoperability between Oracle and Microsoft clouds, IT organizations can avoid complex application redesigns to make use of both platforms. They can also forgo complicated migrations between clouds. For example, a Microsoft application can function in the Oracle Cloud, and an Oracle database on Azure could mean fewer management tasks and tools for the team maintaining it on a separate cloud environment than other IT workloads. Almost a third (29%) of organizations surveyed by research firm ESG cited application redesigns and migrations as key obstacles to wider cloud adoption.

Organizations that develop and deploy custom applications might also benefit from cloud interoperability with the Microsoft and Oracle partnership. These applications can run on both OCI and Azure IaaS offerings. The joint offering promises low latencies between the two clouds, and organizations can mix and match application components as needed.

Tooling in interoperable clouds

In addition to workload migration and expansion across Azure and OCI, subscribers can extend their automation capabilities. Infrastructure-as-code tools, such as HashiCorp Terraform, enable users to build templates to initiate Azure infrastructure and run supported Oracle applications in a cross-cloud configuration.

For example, from one template, a manufacturing team could deploy Oracle’s JD Edwards EnterpriseOne — an ERP suite — on Azure, with an Oracle Autonomous Database running on Oracle’s Exadata cloud infrastructure. This combination yields insights into shop floor processes and supply chains and makes the most of both vendors’ offerings.

Security safeguards

Security is an important consideration for business data, including when it moves across cloud resources.

The Oracle and Microsoft partnership includes a secure, private connection between OCI and Azure. IT teams and security specialists can further strengthen cross-cloud access by using Azure Active Directory to create a federated identity model for authentication and authorization. This service’s access management guarantees a unified authentication mechanism for users and applications.

The rise of cloud vendor partnerships should address some of the burdens that heterogeneous systems and multi-cloud place on IT teams. Interoperability at the vendor level removes some barriers that impede application development and create accessibility headaches. When businesses don’t need to rearchitect applications or undertake highly technical migration steps, they can focus on the best setup for workloads and data to take advantage of what cloud providers offer.

The post How the Microsoft and Oracle partnership affects IT workloads appeared first on Artificial Intelligence.

DataRobot is proudly expanding its enablement operations. We are seeking a technical person who can spearhead enablement efforts in support of our customer-facing engineering team.

In this role you will deeply understand the technologies & processes employed by our customer facing engineers, and in turn teach/train and enable new hires to quickly ramp up to speed.

The successful candidate will have a working knowledge of the various technologies we use to deploy our platform within client-organizations, including but not limited to: Hadoop, Domino, DataBricks, Python, R, C# and Java.

In addition to these deep technical skills, a standout candidate will also have a working knowledge of various statistical and data science / machine learning techniques such as: Data preprocessing, Regression, Classification, Clustering.

This role is based in Boston, MA. Supremely qualified candidates from other geographies in the USA are invited to apply for consideration.

About our field engineers:

A field engineer at DataRobot supports both the sales and data science teams during presales and postsales. Pre-sales activities include but are not limited to security, architecture and POC-related discussions and support. Field Engineers usually have named accounts and are responsible for the successful maintenance of our platform.

About You:

• Excellent writing and communication skills
• Experience installing, managing and supporting platforms running on Linux
• Data management/wrangling or software development experience
• Working knowledge of enterprise software with experience of supporting its deployment in large enterprise accounts
• Bonus: Experience of working with enterprise customers, providing engineering, infrastructure, and technical guidance and support

Additional Bonus points:

• Experience with cloud IaaS providers (AWS EC2, Azure)
• Hadoop, Spark or BI expertise
• Bachelors in Computer Science, related field or equivalent demonstrable experience

The post Technical Enablement Program Manager appeared first on Artificial Intelligence.

The latest research on Human Capital Management Market both qualitative and quantitative data analysis to present an overview of the future adjacency around Human Capital Management Market for the forecast period, 2019-2024. The Human Capital Management market’s growth and developments are studied and a detailed overview is been given. Human Capital Management market will register a 5.9% CAGR in terms of revenue, the global market size will reach US$ 19000 million by 2024, from US$ 14300 million in 2019.

Get Sample Copy of this Report at https://www.reportsintellect.com/sample-request/602262

A thorough study of the competitive landscape of the global Human Capital Management Market has been given, presenting insights into the company profiles, financial status, recent developments, mergers and acquisitions, and the SWOT analysis. It provides a refined view of the classifications, applications, segmentations, specifications and many more for Human Capital Management market. This market research is an intelligence report with meticulous efforts undertaken to study the right and valuable information. Regulatory scenarios that affect the various decisions in the Human Capital Management market are given a keen observation and have been explained.

Some of the leading market players include: SAP SE, Automatic Data Processing, LLC, Ultimate Software Group, Inc., Linkedin (Microsoft), Oracle Corporation.

Reports Intellect projects detail Human Capital Management Market based on elite players, present, past and futuristic data which will offer as a profitable guide for all Human Capital Management Market competitors. Well explained SWOT analysis, revenue share and contact information are shared in this report analysis..

Segmentation by Type: Talent Acquisition, Talent Management, HCM.

Segmentation by application: Healthcare, Financial Services, Government/Non-Profit, Retail/Wholesale, Professional/Technical Services, Manufacturing.

Major Regions: North America, Europe, Asia-Pacific, South America, Middle East and Africa.Top of Form

Table of Contents         

2019-2024 Global Human Capital Management Market Report (Status and Outlook)

1 Scope of the Report
1.1 Market Introduction
1.2 Research Objectives
1.3 Years Considered
1.4 Market Research Methodology
1.5 Economic Indicators
1.6 Currency Considered

2 Executive Summary
2.1 World Market Overview
2.1.1 Global Human Capital Management Market Size 2014-2024
2.1.2 Human Capital Management Market Size CAGR by Region
2.2 Human Capital Management Segment by Type
2.2.1 Talent Acquisition
2.2.2 Talent Management
2.2.3 HR Core Administration
2.2.4 HCM
2.3 Human Capital Management Market Size by Type
2.3.1 Global Human Capital Management Market Size Market Share by Type (2014-2019)
2.3.2 Global Human Capital Management Market Size Growth Rate by Type (2014-2019)
2.4 Human Capital Management Segment by Application
2.4.1 Healthcare
2.4.2 Financial Services
2.4.3 Government/Non-Profit
2.4.4 Retail/Wholesale
2.4.5 Professional/Technical Services
2.4.6 Manufacturing
2.5 Human Capital Management Market Size by Application
2.5.1 Global Human Capital Management Market Size Market Share by Application (2014-2019)
2.5.2 Global Human Capital Management Market Size Growth Rate by Application (2014-2019)

3 Global Human Capital Management by Players

Continued.

Reasons to buy this report:

1. Estimates 2019-2024 Human Capital Management Market development trends with the recent trends and SWOT analysis.
2. Obtain the most up to date information available on all active and planned Human Capital Management Market globally.
3. Understand regional Human Capital Management Market supply scenario.
4. Identify opportunities in the global Human Capital Management Market industry with the help of upcoming projects and capital expenditure outlook.
5. Facilitate decision making on the basis of strong historical and forecast of Human Capital Management Market capacity data.

The post Human Capital Management Market research is an intelligence report by: SAP SE, Automatic Data Processing, LLC, Ultimate Software Group, Inc., Linkedin (Microsoft), Oracle Corporation. appeared first on Artificial Intelligence.