This is one part of a four-part introductory series about autonomous systems. To learn more, read the rest of the series and the free e-book linked at the bottom of this post.
In manufacturing, the name of the game is optimization. With many complex processes working together to build a product or solve a logistical issue, cutting even a little waste can turn into big savings over days, weeks and months.
A major revolution in manufacturing optimization was automation, in which machines carried out the process of building products without as much human intervention. As the manufacturing sector grows, businesses look for more ways to make building products easier and more cost-effective.
That’s where autonomous systems come in. By adding AI to machines, processes or lines, manufacturers have a new weapon in their fight for optimization and efficiency. Engineers are using these new tools that can adjust to their environments and adapt in real time to better meet operational objectives. This stands to disrupt not only how we think about industrial processes, but how humans and machines can work together for maximum impact.
Autonomy, control systems and advancements in AI
Manufacturers know that there are limits to automation—namely, that it’s limited in flexibility and requires high levels of precision and unchanging operating conditions. Think about a modern car assembly line: As a car moves down the line, everything must be just right: location, angle, position. If something is even slightly off, the machines responsible for any aspect of that car can, and probably will, miss their mark (or signal for a human to intervene).
The next step in the evolution of these automated systems is “autonomous” systems. Instead of the automation of a predetermined set of steps, autonomous systems use AI to learn from their environments and engage them dynamically. These machines adopt strategies, rather than rote recipes for action, and then execute them in response to their environment.
The Microsoft approach to autonomous systems
Intelligent, autonomous machines can learn to account for challenges like resource scarcity, managing fail-safe conditions and adaptive object manipulation. To accelerate this learning, Microsoft has pioneered a method that allows control and process experts to teach the AI agent using their own expertise. This allows the AI agent to learn similarly to how a human would: a little at a time, based on a lesson plan from an expert. This includes getting feedback and using that feedback to improve. This AI training methodology allows the most expert engineers to impart their wisdom to the AI agent without needing a data science background, to get the AI agent trained quickly.
The AI agent can then be deployed to assist or advise humans or even work autonomously to optimize a system or process to significantly reduce waste, cost and time.
Companies collaborate on one of Australia’s largest digital twin, emissions reduction initiatives, and drive transformative operational models
Telstra-Microsoft partnership signals new generation digital foundations for Australian businesses.
SYDNEY and REDMOND, Wash. — Sept. 25, 2020 — Microsoft Corp. and Telstra have extended their long-standing strategic partnership to focus on accelerating the development and release of innovative and sustainable cloud-based solutions across multiple industries driving efficiency, amplifying decision making capability and enhancing customer experiences.
The partnership is founded on Telstra and Microsoft’s shared understanding that cloud, combined with 5G, will enable intelligent devices to be securely deployed on a much greater scale. Combining Microsoft Azure and Telstra’s network also supports Australian developers and independent software vendors (ISVs) as they develop solutions that leverage AI, low latency and increased resilience.
This will help enterprises build end-to-end digital processes and enable completely new transformative business models that leverage data to accelerate smart decision making, maximise business opportunities and grow revenues. Telstra and Microsoft will partner to:
harness IoT, Edge, AI and digital twin capability to develop important new industry solutions in areas such as asset tracking, supply chain management, telematics and smart spaces;
leverage Azure as preferred cloud for Telstra’s ongoing internal digital transformation.
explore and pursue technology and data-driven solutions to advance our sustainability and climate commitments and
build ground-breaking, nationally important solutions that leverage the Telstra Data Hub.
The companies will partner on digital twins for Telstra customers as well as for Telstra’s own commercial buildings and selected other infrastructure – which when fully deployed will be one of the largest Azure-based digital twins in Australia. Telstra’s digital twin will map physical environments in an online virtual setting, to create models that provide at-a-glance understanding of what is happening in the real world, and support improved what-if scenario planning.
Telstra is working with Microsoft as its preferred cloud provider for ongoing internal digital transformation. Azure will provide the digital foundations for Telstra’s strategic plan to streamline and simplify operations, transitioning from legacy and on-premises applications to modern cloud-based solutions.
Telstra CEO Andrew Penn said the strategic partnership brought together the best strengths of the two organisations.
“We already have a longstanding relationship with Microsoft and have worked together in areas that are market-leading to create unique experiences for our customers. Over the past 18 months, we have exclusively launched Xbox All Access for Australian gamers, were the first to launch Telstra Calling for Office 365, the only native Teams voice calling plan in Australia, which we recently expanded to include Microsoft Business Voice for SMB customers; and co-collaborated on Telstra Data Hub to help industries better manage their data securely.”
“Today’s announcement with Microsoft formalises the several streams of work we are already collaborating on. The global scale of Microsoft’s platform, tools, and applications, together with Telstra’s network solutions, reliability and leadership, will drive new and unique solutions for Australia,” Mr Penn said.
“In July, Telstra was certified carbon neutral in our operations. Significantly reducing emissions while the demand for connectivity and new digital technologies is rising rapidly is one of our biggest commitments, as well as one of our biggest challenges. Microsoft and Telstra both have ambitious climate targets and share a commitment to a net zero carbon future.”
“The outputs from all workstreams will also help deliver more innovative products for customers across all segments of the market, and will aim to enhance customer experience and engagement, solve business challenges, and drive a new level of technology leadership. This is a great opportunity to drive further digital innovation to strengthen the Australian economy, and to build a sustainable, connected future so everyone can thrive,” Mr Penn said.
“The broad adoption of cloud and 5G technology will create new opportunities for businesses worldwide, including in Australia,” said Satya Nadella, CEO, Microsoft.
“We’re expanding our partnership with Telstra and bringing together the power of Azure and Telstra’s network to build new solutions in critical areas like asset tracking, supply-chain management, and smart spaces, harnessing the latest advances in AI, digital twins, and mixed reality.”
# Notes to the Editor #
Focus areas of the extended partnership include, but are not limited to:
Digital twin, IoT and cloud: Telstra has selected Microsoft as a strategic partner in the design and build of a scalable and unified IoT platform leveraging Azure IoT that enables Telstra to simplify operations and significantly reduce time to market. Telstra is partnering with Microsoft to build a digital twin across its own commercial buildings with an initial deployment of five buildings including the flagship site at 242 Exhibition St in Melbourne. When fully deployed this represents one of the largest Azure-based digital twins in Australia. Once complete, the digital twin will allow Telstra to establish a digital nerve centre that promises enhanced transparency by modernising business processes and the work environment, enhancing digital interaction between personnel and enabling Telstra to improve operational efficiency.
Using its technology services provider, Telstra Purple, Telstra is working with Microsoft to provide an advanced digital twin solution for Downer Group’s asphalt plants. This ‘digital asphalt plant’; promises greater efficiency, reliability, and safety while at the same time increasing operational transparency and control. Through a collaborative design process, Telstra Purple and Downer identified the opportunity to leverage Microsoft Azure AI and edge services and Telstra’s Smart Spaces video analytics, to provide real time worker safety information directly to Azure Digital Twins. These ‘digital safety barriers’ identify and track dangerous activity across the plant. The companies envision the solution will be deployed in 33 asphalt plants across Australia.
Digital Foundation: Telstra is working with Microsoft Azure as its preferred cloud provider for ongoing internal digital transformation. Azure will provide the digital foundations for Telstra’s strategic plan to streamline and simplify operations, transitioning from legacy and on-premise applications to modern cloud-based solutions.
Telstra is expanding its use of Azure for several critical IT applications, including the creation of a Digital Foundation for the ongoing modernisation of IT infrastructure, and also underpinning Data Hub, IoT and Digital Twin Capability. Azure will also help Telstra achieve its sustainability targets.
Sustainability: Addressing climate change is one of the defining challenges of the decade. Our sector has the potential to enable emissions savings more than seven times greater than the emissions we generate through providing our customers with low carbon products and services such as cloud computing.
Telstra and Microsoft are committed to exploring and pursuing technology and data-driven work to advance our sustainability and climate commitments. The initial focus will be on reducing emissions, circular economy, and remote work. We will work together to pilot real-time data reporting solutions such as Microsoft’s Sustainability Calculator that will deliver greater understanding of our joint carbon footprint to achieve further emissions reductions.
Armed with that insight the companies will be able to identify and support the development of more efficient products and processes.
Telstra Data Hub (TDH): Collaborating over the past year, Microsoft and Telstra have made significant progress with the Telstra Data Hub which enables many-to-many data interconnects to occur through a common platform. Designed to facilitate complex data sharing and permission scenarios, while alleviating the need to create multiple, bespoke point-to-point integrations required between systems, Telstra Data Hub has been built using the companies’ technologies to help customers realise the value of their data, to share their data across industry and act as the foundation for new AI models.
Early customers include the Queensland State government, who are evaluating how to securely gather the critical data to manage the state’s natural water system, and in doing so not only develop an end-to-end view of the state’s water asset but to also provide immediate value to the industries that use the water to fuel the economy. Other users of Telstra Data Hub include the Victor Chang Cardiac Research Institute, where we are collaborating on a data sharing and analytics ecosystem focused on understanding sudden cardiac death in young people, as well as with Charles Sturt University on a data ecosystem for agricultural commodities.
Telstra
Telstra is Australia’s leading telecommunications and technology company, offering a full range of communications services and competing in all telecommunications markets. Our purpose is to build a connected future so everyone can thrive.
Microsoft
Microsoft (Nasdaq “MSFT” @microsoft) enables digital transformation for the era of an intelligent cloud and an intelligent edge. Its mission is to empower every person and every organisation on the planet to achieve more.
Media enquiries, contact:
Rudolf Wagenaar, Commercial Communications Lead, Microsoft Australia
The art world may not be the first business sector that comes to mind when you think about applications of AI, but a new algorithm developed by Microsoft and MIT is proving to be quite the curator.
Microsoft Research Development Engineer Mark Hamilton is a PhD student at MIT.
Microsoft Research Development Engineer Mark Hamilton , who is also a PhD student at MIT, helped develop the algorithm, which can find similarities in color, texture, theme and meaning between otherwise disparate works of art. The algorithm was recently highlighted by Smithsonian Magazine and several other publications. We chatted with Hamilton to learn more about the project and how it could be broadly applied to other areas.
Blog: Why art?
Mark: I love art, and we had a previous collaboration with the Metropolitan Museum of Art that let you explore an exhibit, understanding similarities between works of art and visualizing the space between various pieces. MosAIc was inspired by an exhibit that paired art from two artists who never met and showed that they have very similar structure. We thought we could do that on a larger scale, and we are continuing to be surprised by some of the connections we are able to find.
Blog: The algorithm can find similar works of art within specific styles or media based on colors, shapes and content, as well as meaning and themes. How can an algorithm take meaning and themes into account?
Mark: Today’s vision algorithms behave a lot like we do. When we look at an image, we get a gut feel for what it contains, such as the objects, people and composition. We train our neural network to understand thousands of objects across millions of different real-world scenes. We then feed that algorithm artworks and capture its ideas, or gut feel, about these works. These neural network ideas have even been shown to be similar to the ideas that humans have about images. It’s these neural network ideas that allow us to compare the content of different works of art.
Blog: What is new and innovative about the MosAIc algorithm?
Mark: One of the new contributions of the work is a new type of algorithm we call a conditional image retrieval system. If you think about something like reverse image search, you put in an image and find all the similar images from the web. What we have done is allow you to find not only the most similar items across the whole collection, but also any sub-collection such as the Egyptian artworks, the prints or even the works by an individual artist. This allows us to find matches across widely different artistic traditions, which is something that regular approaches cannot do efficiently. More technically, we created a data structure that generalizes K-Nearest Neighbor trees to allow them to specialize to particular sub-collections quickly and efficiently.
Blog: In what other ways could it be used?
Mark: At the core of this, you have a new kind of search technology that can be applied to any data. The data can be images like art, products or really anything you want. One example from retail would be a fashion aware search; you could take your favorite pair of pants and use this approach to find the best matching blouse. In the realm of text and documents, let’s say you have an email that is talking about a given topic. Using our approach, you could pull up all of the memos or receipts with similar content as the email. To make these systems, one could just swap out our vision networks with equivalent networks for text, music or other data.
This approach also gives you the ability to add diversity to your search engines in a controlled and structured way. For example, you could imagine showing not only the top results for a restaurant search, but also top results from other sub-categories like vegetarian food, or Black or African American owned restaurants. This way you can supply results that are relevant and highlight many diverse types of content.
Blog: How can people learn more about this project?
Behind each technological innovation, there is a person with a dream that they are determined to bring to fruition. Today we are excited to launch a new community and series that tells the stories of incredible heroes from all walks of life who are innovating to help solve some of society’s biggest challenges.
Their stories shine a light on discovering what is possible when big hearts, inspirational ideas and innovative technologies converge. We know that technology doesn’t change the world, people do. AI is a game-changing tool that enables people and organizations to solve complex social, health and environmental challenges. With the growing accessibility of AI, we’re seeing this in action—humans accelerating meaningful innovation to improve lives and benefit the planet. These are stories of hope and human empowerment.
Meet our AI heroes
Our first four stories are dedicated to people who are innovating to fight COVID-19. Visit the site to see how they are using AI to combat the virus on multiple fronts, then chat with them live on Sept. 15 during a LinkedIn Live event, followed by a #MicrosoftAIChat on Twitter. They are, from left to right in the image above:
Meet Hadas Bitran: When COVID-19 ravaged the world, she saw a great need to help frontline healthcare workers by developing a COVID-19 self-assessment bot that enables people to check their symptoms before going to a medical appointment.
Meet Dr. Greg Bowman: When COVID-19 started, his lab decided to use their army of citizen scientists and Microsoft AI to advance research and accelerate potential treatments.
Meet Kelvin Summoogum: He founded MiiCare, a digital companion for the elderly that helps them live safely and independently.
Meet Alice Piterova: In the time of COVID-19, she and her cohort at AI for Good UK created an AI model that simulates the spread of COVID-19 in refugee camps.
Here’s how you can be a part of the conversation on Sept. 15:
LinkedIn Live at 8:15 am PT: Influencer and futurist Bernard Marr will be joined by the first four individuals featured in the Humans and AI series. Tune in live on Marr’s LinkedIn page for the live video to ask questions and meet these inspirational individuals.
Twitter chat at 9 am PT: The conversation continues on Twitter with the #MicrosoftAIChat hosted by Marr, Bitran, Bowman, Piterova and Summoogum. This Twitter chat will discuss #HumansAndAI and will be a forum for anyone to meet our team and share ideas on how technology can be applied to challenges and problems we collectively face as a united global community.
How to join the Twitter Chat:
Never participated in a Twitter chat? Welcome! We’ll ask the following five questions starting at 9 am PT on Sept. 15. Anyone can join in by sharing and answering:
If you could launch an AI startup, what would it be? And “@” tag anyone you want to partner with in your reply.
What problem or societal challenge drives your innovation?
Why is AI a potential tool for solving societal challenges?
What is the most inspiring use of AI you have seen?
Do you know an incredible #HumansAndAI leader or do you have a story to share?
You can share the questions with your community or answer by quote retweeting the tweets and adding your answer + tagging the tweet with #MicrosoftAI and #HumansandAI. To follow the conversation once we get started on Twitter, just type #MicrosoftAI #HumansandAI into the search bar, or click this link to find the chat on Twitter.
This is the final article to the series demonstrating Perl with Tic-Tac-Toe. This article provides a module that can compute better game moves than the previously presented modules. For fun, the modules chip1.pm through chip3.pm can be incrementally moved out of the hal subdirectory in reverse order. With each chip that is removed, the game will become easier to play. The game must be restarted each time a chip is removed.
An example Perl program
Copy and paste the below code into a plain text file and use the same one-liner that was provided in the the first article of this series to strip the leading numbers. Name the version without the line numbers chip3.pm and move it into the hal subdirectory. Use the version of the game that was provided in the second article so that the below chip will automatically load when placed in the hal subdirectory. Be sure to also include both chip1.pm and chip2.pm from the second and third articles, respectively, in the hal subdirectory.
00 # artificial intelligence chip
01 02 package chip3;
03 require chip2;
04 require chip1;
05 06 use strict;
07 use warnings;
08 09 sub moverama {
10 my $game = shift;
11 my @nums = $game =~ /[1-9]/g;
12 my $rama = qr/[1973]/;
13 my %best;
14 15 for (@nums) {
16 my $ra = $_;
17 next unless $ra =~ $rama;
18 $best{$ra} = 0;
19 for (@nums) {
20 my $ma = $_;
21 next unless $ma =~ $rama;
22 if (($ra-$ma)*(10-$ra-$ma)) {
23 $best{$ra} += 1;
24 }
25 }
26 }
27 28 @nums = sort { $best{$b} <=> $best{$a} } keys %best;
29 30 return $nums[0];
31 }
32 33 sub hal_move {
34 my $game = shift;
35 my $mark = shift;
36 my @mark = @{ shift; };
37 my $move;
38 39 $move = chip2::win_move $game, $mark, \@mark;
40 41 if (not defined $move) {
42 $mark = ($mark eq $mark[0]) ? $mark[1] : $mark[0];
43 $move = chip2::win_move $game, $mark, \@mark;
44 }
45 46 if (not defined $move) {
47 $move = moverama $game;
48 }
49 50 if (not defined $move) {
51 $move = chip1::hal_move $game;
52 }
53 54 return $move;
55 }
56 57 sub complain {
58 print 'Just what do you think you\'re doing, ',
59 ((getpwnam($ENV{'USER'}))[6]||$ENV{'USER'}) =~ s! .*!!r, "?\n";
60 }
61 62 sub import {
63 no strict;
64 no warnings;
65 66 my $p = __PACKAGE__;
67 my $c = caller;
68 69 *{ $c . '::hal_move' } = \&{ $p . '::hal_move' };
70 *{ $c . '::complain' } = \&{ $p . '::complain' };
71 72 if (&::MARKS->[0] ne &::HAL9K) {
73 @{ &::MARKS } = reverse @{ &::MARKS };
74 }
75 }
76 77 1;
How it works
Rather than making a random move or making a move based on probability, this final module to the Perl Tic-Tac-Toe game uses a more deterministic algorithm to calculate the best move.
The big takeaway from this Perl module is that it is yet another example of how references can be misused or abused, and as a consequence lead to unexpected program behavior. With the addition of this chip, the computer learns to cheat. Can you figure out how it is cheating? Hints:
References allow data to be modified out of scope.
Final notes
Line 12 demonstrates that a regular expression can be pre-compiled and stored in a scalar for later use. This is useful as performance optimization when you intend to re-use the same regular expression many times over.
Line 59 demonstrates that some system library calls are available directly in Perl’s built-in core functionality. Using the built-in functions alleviates some overhead that would otherwise be required to launch an external program and setup the I/O channels to communicate with it.
Collaboration will build pathways to financial security and provide tools for sustainable growth
PURCHASE, N.Y., and REDMOND, Wash. — July 28, 2020— On Tuesday, Mastercard and Microsoft Corp. announced a collaboration to shape the future of digital commerce, drive startup innovation and enable financial inclusion. The collaboration will accelerate Mastercard Labs’ cloud native research and development activities, enabled by Azure and AI, to advance Mastercard Labs’ mission to de-risk and commercialize emerging technologies and platforms for digital commerce. Through access to technical expertise and cutting-edge technologies, Mastercard’s partners will be further empowered to build and securely scale new solutions.
“We are thrilled to deepen our longstanding relationship with Microsoft by advancing the research, development and scaling of new technologies and business models,” said Ken Moore, executive vice president and head of Mastercard Labs. “This strategic collaboration will strengthen and extend our cloud services and capabilities for clients and fintech partners, sparking innovation and creativity for the ecosystem. It will enable us to explore opportunities focused on new client segments, technologies and trends as we continue to drive financial inclusion and build the future of commerce.”
“Mastercard’s commitment to innovation and financial inclusion has accelerated digital commerce for individuals and businesses around the world,” said Judson Althoff, executive vice president of Microsoft’s Worldwide Commercial Business. “We look forward to building on our strong relationship and accelerating co-innovation to help connect and power a digital economy for everyone, everywhere.”
Empowering fintech innovation, advancing digital commerce
Capitalizing on Mastercard’s global network and leveraging Azure’s global reach, the collaboration will enable Mastercard’s ecosystem of partners to explore the use of emerging innovations and new commerce capabilities such as devices that enable digital payments in new ways. Through access to Azure technologies, augmented and virtual reality and Internet of Things, fintech partners will be empowered to create new user experiences to advance how consumers, businesses and governments exchange value.
Mastercard’s Start Path program has assisted with the development of over 230 fintech companies worldwide, democratizing access to financial services. Building on that momentum, the collaboration will expand support for the fintech community by helping diversify and build new businesses, and create and scale new cloud-first digital products and services.
Enabling financial inclusion
Mastercard and Microsoft share a commitment to ensuring people in underserved communities have access to digital products and services to realize their full potential. The collaboration will advance Mastercard’s vision to improve the lives of people by building pathways to financial security and access to critical services. The Azure cloud environment will serve as the native infrastructure for Mastercard Labs’ inclusion efforts and support Mastercard Community Pass — a platform that pulls together complex ecosystems and provides underserved communities with access to essential services, such as education, agriculture marketplaces and basic healthcare.
Microsoft Azure provides Mastercard — and the ecosystems they jointly serve — with a scalable and flexible platform imperative for establishing secure connections and protecting data, co-innovating with partners and delivering access to financial services
About Mastercard
Mastercard (NYSE:MA) is a global technology company in the payments industry. Our mission is to connect and power an inclusive, digital economy that benefits everyone, everywhere by making transactions safe, simple, smart and accessible. Using secure data and networks, partnerships and passion, our innovations and solutions help individuals, financial institutions, governments and businesses realize their greatest potential. Our decency quotient, or DQ, drives our culture and everything we do inside and outside of our company. With connections across more than 210 countries and territories, we are building a sustainable world that unlocks priceless possibilities for all.
Microsoft (Nasdaq “MSFT” @microsoft) enables digital transformation for the era of an intelligent cloud and an intelligent edge. Its mission is to empower every person and every organization on the planet to achieve more.
For more information, press only:
Microsoft Media Relations, WE Communications for Microsoft, (425) 638-7777, [email protected]
Mastercard Global Communications, Jen Langione, (917) 408-2941, [email protected]
Note to editors: For more information, news and perspectives from Microsoft, please visit the Microsoft News Center at http://news.microsoft.com. Web links, telephone numbers and titles were correct at time of publication, but may have changed. For additional assistance, journalists and analysts may contact Microsoft’s Rapid Response Team or other appropriate contacts listed at https://news.microsoft.com/microsoft-public-relations-contacts.
NEW YORK and REDMOND, WA – July 23, 2020 – MSCI Inc. (NYSE: MSCI) and Microsoft Corp. have formed a strategic alliance to accelerate innovation among the global investment industry. By bringing together the power of Microsoft’s cloud and AI technologies with MSCI’s global reach through its portfolio of investment decision support tools, the companies will unlock new innovations for the industry and enhance MSCI’s client experience among the world’s most sophisticated investors, including asset managers, asset owners, hedge funds and banks.
Initially, the companies will focus on migrating MSCI’s existing products, data and services onto Azure as its preferred cloud platform in stages, starting with its Index and Analytics solutions followed by its Environmental, Social and Governance (ESG) products and ratings; Real Estate data and solutions; and MSCI’s risk analytics platform Beon. By modernizing MSCI’s data and analytics services and infrastructure, the companies will be able to deliver new capabilities which will help investors more swiftly and efficiently manage data and understand the drivers of risk and performance.
In addition, MSCI and Microsoft will explore collaboration opportunities to drive climate risk and ESG solutions, leveraging Microsoft’s Azure and Power Platform and MSCI’s ESG and climate solutions capabilities. This future collaboration, in line with both organizations’ commitment to sustainability, is intended to help investors better understand and interpret the business risks and opportunities that climate change brings.
“Investors’ needs to rapidly innovate and adapt as strategies and business models evolve, build and manage big data, and improve operational efficiencies are growing at a critical speed around the world,” said Henry Fernandez, Chairman and CEO of MSCI. “Our strategic alliance with Microsoft underscores MSCI’s commitment to driving relentless innovation in the technology of our products and services to help investors achieve their desired investment outcomes.”
“Our strategic collaboration with Microsoft is the latest step in our long and established heritage of innovation and we are excited about the long-term potential of this relationship,” added Jigar Thakkar, Chief Technology Officer and Head of Engineering at MSCI. “MSCI is a future-focused business and Azure enables us not just to enhance our capabilities and client solutions of today, but also provide the platform to accelerate our journey in building world-class technology and tools to solve the investment industry’s challenges of tomorrow.”
“Investors rely on cutting-edge technologies to deliver intelligent insights, manage risk and detect anomalies so they can help customers achieve their investment goals,” said Scott Guthrie, Executive Vice President, Cloud +AI, Microsoft. “By harnessing the power of Azure and its AI capabilities, together with MSCI’s expertise and position within the investment ecosystem, we will be able to accelerate new innovations that help investors better optimize their clients’ performance capabilities.”
“This alliance opens exciting frontiers for the global investment community,” said Merrie Williamson, Microsoft VP of Azure Apps and Infrastructure. “The combination of MSCI’s relentless pursuit of innovation with Microsoft’s deep data expertise, expansive partner ecosystem, and go-to-market capabilities forms an alliance with the potential to accelerate the investment industry.”
About MSCI MSCI is a leading provider of critical decision support tools and services for the global investment community. With over 45 years of expertise in research, data and technology, we power better investment decisions by enabling clients to understand and analyze key drivers of risk and return and confidently build more effective portfolios. We create industry-leading research-enhanced solutions that clients use to gain insight into and improve transparency across the investment process. To learn more, please visit www.msci.com.
About Microsoft Microsoft (Nasdaq “MSFT” @microsoft) enables digital transformation for the era of an intelligent cloud and an intelligent edge. Its mission is to empower every person and every organization on the planet to achieve more.
For more information, press only:
Microsoft Media Relations, WE Communications for Microsoft, (425) 638-7777, [email protected]
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Forward-Looking Statements
This press release contains forward-looking statements within the meaning of the Private Securities Litigation Reform Act of 1995. These forward-looking statements relate to future events or to future financial performance and involve known and unknown risks, uncertainties and other factors that may cause actual results, levels of activity, performance or achievements to be materially different from any future results, levels of activity, performance or achievements expressed or implied by these statements. In some cases, you can identify forward-looking statements by the use of words such as “may,” “could,” “expect,” “intend,” “plan,” “seek,” “anticipate,” “believe,” “estimate,” “predict,” “potential” or “continue,” or the negative of these terms or other comparable terminology. You should not place undue reliance on forward-looking statements because they involve known and unknown risks, uncertainties and other factors that are, in some cases, beyond MSCI’s control and that could materially affect actual results, levels of activity, performance or achievements.
Other factors that could materially affect actual results, levels of activity, performance or achievements can be found in MSCI’s Annual Report on Form 10-K for the fiscal year ended December 31, 2019 filed with the Securities and Exchange Commission (“SEC”) on February 18, 2020 and in quarterly reports on Form 10-Q and current reports on Form 8-K filed or furnished with the SEC. If any of these risks or uncertainties materialize, or if MSCI’s underlying assumptions prove to be incorrect, actual results may vary significantly from what MSCI projected. Any forward-looking statement in this press release reflects MSCI’s current views with respect to future events and is subject to these and other risks, uncertainties and assumptions relating to MSCI’s operations, results of operations, growth strategy and liquidity. MSCI assumes no obligation to publicly update or revise these forward-looking statements for any reason, whether as a result of new information, future events, or otherwise, except as required by law.
Together the companies aim to build tighter connections between consumers and farmers through innovative new technologies built on Microsoft’s cloud
ARDEN HILLS, Minn., and REDMOND, Wash. — July 15, 2020 — Land O’Lakes Inc. and Microsoft Corp. on Wednesday announced a multiyear strategic alliance to pioneer new innovations in agriculture and enhance the supply chain, expand sustainability practices for farmers and the food system, and close the rural broadband gap. As one of the nation’s largest farmer-owned cooperatives with 150 million acres of productive cropland in its network, Land O’Lakes is deeply connected to rural America and has a unique understanding of farmers’ needs and the communities where they and their families live and work. Combined with Microsoft’s trusted cloud technologies and AI capabilities, the companies will deliver solutions that help farmers’ profit potential and adoption of sustainable agricultural practices.
According to the U.S. Department of Agriculture, U.S. farms contribute more than $130 billion to the economy, emphasizing the critical role farmers play in our nation’s food supply. Yet the industry faces challenges that threaten its viability, including climate change, trade issues and an evolving workforce. With the emergence of COVID-19, the industry is increasingly facing production and supply-chain issues, and many farmers are facing new economic challenges for their family-owned businesses.
“Land O’Lakes is one of the most important food suppliers in the U.S., and our nation’s farmers and consumers rely on its ability to rapidly adapt to changing market forces through innovation,” said Satya Nadella, CEO, Microsoft. “Through our partnership, we will apply the power of Azure and its AI capabilities to help Land O’Lakes solve some of the most pressing challenges facing the industry and bridge the divide between rural and urban communities.”
“As America’s farmers continue to deliver the world’s safest, most affordable food supply, they face an increasing number of obstacles that are beyond their control. The data-based, precision agriculture tools that we are building with Microsoft will provide the edge they need, but unreliable or nonexistent high-speed internet in rural areas keeps these tools out of reach for many. Through this alliance, we will work to address this need and help farmers remain profitable and sustainable,” said Beth Ford, president and CEO of Land O’Lakes, Inc.
Accelerating agriculture innovation
Initially, the companies will focus on developing a connected AgTech platform, built on Microsoft Azure, that will bring together Land O’Lakes’ portfolio of innovative AgTech tools, such as WinField United’s R7® Suite, Data Silo and Truterra™ Insights Engine under one unified architecture. By standardizing on Azure and harnessing the power of Azure FarmBeats, Land O’Lakes will be able to derive insights that enable intelligent agriculture solutions for farmers to be more productive with their time and resources. This includes early mitigation of plant stress to guide precisely where and when farmers should take action on their field for ideal growth conditions, maximization of yield potential by planting the right seed varieties and nutrients, optimizing fertilizer investments, and ensuring accurate output ratio to meet demand properly, all while lowering the farm carbon footprint.
Built on top of the AgTech platform, the companies will collaborate to advance an aggregator of data with Data Silo, as well as leverage Microsoft Azure and its AI capabilities and insights from WinField United Answer Plot® test fields, to support more predictable decisions for placement of crop inputs such as seeds and treatments, with the goal of increasing return on investment with the entire acre.
The companies will create a Digital Dairy solution, harnessing the power of edge computing to capture data from farms with poor internet coverage, and the power of AI to provide data-driven insights for dairy producers. This initiative will bring together multiple data streams — including weather, feed management and animal health — from sensors and third-party applications to help dairy producers improve profit potential, adopt conservation practices and reduce waste by feeding livestock only what they need and ensuring milk supply doesn’t go bad in the supply chain. Through the Digital Dairy solution, the companies will enable Traceability throughout the Land O’Lakes supply chain, providing transparency to milk, butter and cheese, ensuring consumer confidence that foods are of the highest quality and sustainably sourced. At a time when the dairy industry is stressed with changing customer demand and supply-chain disruptions, these digital tools will help producers improve efficiencies and profit potential, while helping to ensure food gets to the people who need it most.
Advancing sustainability initiatives
With the challenges of a changing climate, more extreme weather and a growing world population, Land O’Lakes and Microsoft share a commitment to sustainability and natural resources stewardship to help farm fields be both more resilient and productive for generations to come. We can help farmers improve the health and function of their farms’ soils to both produce more food and store greenhouse gas, including carbon. The Food and Agriculture Organization of the United Nations estimates that agricultural soils could hold up to 10% of human-caused emissions within 25 years. Yet, soils are largely absent from global carbon markets. As a result, farmers lack adequate information and incentives to practice regenerative agriculture to capture and store carbon.
The companies are working together to change that by developing a technology suite to help farmers improve their profit potential and generate new revenue in carbon markets. The new alliance will develop capabilities to quickly and effectively predict the carbon benefits of regenerative practices like no-till, precision nutrient management and planting of cover crops. Combining such capabilities with the real-time transparency from remote sensing and satellite data will make certification of these projects in global carbon markets easier, quicker and less expensive — ultimately maximizing the economic value for farmers.
The companies will explore integrating these new capabilities into the Truterra™ Insights Engine to create a unique soil health platform that can help farmers identify new opportunities to adopt practices to improve the quality and function of their farms’ soils, estimate the natural resource and economic benefits of those new practices, generate soil carbon credits, and connect to soil carbon markets that sell certified credits to buyers.
The platform would help unlock the potential of hundreds of millions of acres of farmland to be an effective carbon removal system and improve soil health and productivity, while providing farmers with the insights they need to make the best decisions for their farms. Markets like these may help Microsoft reach its goal to be carbon negative by 2030 and remove more carbon from the atmosphere than it emitted since its founding by 2050, and help other businesses take advantage of soil carbon credits and the market to reduce their greenhouse gas emissions.
Connecting rural America
Broadband is essential to fully participate in the modern economy. Unfortunately, more than 18 million Americans, 14 million of whom live in rural communities, don’t have access to broadband connections. Both companies are working to connect rural communities: Microsoft’s Airband Initiative has worked around the country to eliminate the rural broadband gap, and Land O’Lakes’ American Connection Project aims to close the digital divide through action and advocacy.
The companies are launching pilots that will lead to long-term programmatic solutions in rural communities. Combining Microsoft’s Airband program and specific locations within the Land O’Lakes owner network, broadband will be deployed to rural communities along with services including telehealth, educational resources and digital skilling. Both companies are also advocating for policy changes to accelerate the availability of broadband in rural communities, including broadband mapping to fully understand who has and does not have access to broadband, and federal funding in upcoming legislation.
Unfortunately, the COVID-19 pandemic makes the digital divide even worse for many people. Remote work, education and healthcare are out of reach for people living in rural communities without online access. The companies are answering this immediate need for connectivity by working together to turn on free public Wi-Fi at more than 150+ locations in 19 states using a mix of technologies, including fixed wireless, and supplying internet service providers with the necessary hardware.
Land O’Lakes to transition its IT platforms to Microsoft
Through this agreement, Microsoft becomes Land O’Lakes’ strategic cloud provider, and Land O’Lakes will migrate the majority of the company’s IT infrastructure onto Microsoft Azure. The company has enabled Microsoft 365 and Teams for its workforce, empowering them with next-generation digital experience technology for increased productivity, advanced security, internal collaboration and customer engagement.
About Land O’Lakes Inc.
Land O’Lakes, Inc., one of America’s premier agribusiness and food companies, is a member-owned cooperative with industry-leading operations that span the spectrum from agricultural production to consumer foods. With 2019 annual sales of $14 billion, Land O’Lakes is one of the nation’s largest cooperatives, ranking 232 on the Fortune 500. Building on a legacy of more than 99 years of operation, Land O’Lakes today operates some of the most respected brands and businesses in agriculture and food production including Land O’Lakes Dairy Foods, Purina Animal Nutrition, WinField United and Truterra, LLC. The company does business in all 50 states and more than 60 countries. Land O’Lakes, Inc. corporate headquarters are located in Arden Hills, Minn.
About Microsoft
Microsoft (Nasdaq “MSFT” @microsoft) enables digital transformation for the era of an intelligent cloud and an intelligent edge. Its mission is to empower every person and every organization on the planet to achieve more.
For more information, press only:
Microsoft Media Relations, WE Communications for Microsoft, (425) 638-7777, [email protected]
Land O’Lakes Media Relations, Brooke Dillon, (651) 202-1670, [email protected]
Note to editors: For more information, news and perspectives from Microsoft, please visit the Microsoft News Center at http://news.microsoft.com. Web links, telephone numbers and titles were correct at time of publication, but may have changed. For additional assistance, journalists and analysts may contact Microsoft’s Rapid Response Team or other appropriate contacts listed at https://news.microsoft.com/microsoft-public-relations-contacts.
Four years ago, I joined the startup Bonsai, which envisioned a new way of training AI agents. The idea was to enable subject matter experts to use their knowledge of a particular problem to teach the AI agent how to make decisions about it, or to create an optimal control policy. Bonsai chose reinforcement learning (RL) as the first AI category to support, as we believed it could enable new use cases for automation and create significant value for future customers.
Before then, reinforcement learning had mostly received attention for teaching AI agents how to play games like Pong and other Atari classics. Then, OpenAI enabled users with a library of example environments that could be used to learn more about RL and increase performance of the latest RL algorithms. Soon thereafter, examples of simple physics-based models were added, either as simple robotic systems or games that took advantage of built-in physics engines. At Bonsai, we accelerated that trend and focused on teaching AI agents how to become more intelligent controllers for advanced control problems where traditional approaches may have shortcomings.
With a vision of developing an AI toolchain that enables engineers to add intelligence to their existing and future systems, we started to take a broader view of what might be possible. This goes back to the question: What is a controller? Is a supply chain or any other business process a controller? If so, could we make these controllers more intelligent?
I found a simulation model of the Beer Distribution Game on AnyLogic’s cloud platform and connected it to our deep reinforcement learning service to see if we could teach an AI agent to learn a successful control policy for one of the standard models taught in business school when supply chains are covered. It worked! It easily beat our co-workers when playing the game in real time and enabled our sales team to sign our first supply chain customer.
Fast forward to May 2020. After being acquired by Microsoft in 2018, Bonsai recently launched as a fully integrated Azure service at Microsoft’s Build developers conference. Over the past two years, we have continued to invest in our partnership with AnyLogic, and have learned more about how to use multi-method models with a deep reinforcement learning service such as ours.
If you’re not familiar with RL, it’s based on the idea of framing problems as a Markov decision process in which an AI agent learns a control policy to always pick the best possible action for a given state of the system. Ideally this system is somewhat random and dynamic, which makes a reward-based learning approach superior compared with other traditional control theories. More details can be found here.
A simplistic factory floor model where cost associated with product processing is calculated and analyzed using activity-based costing (ABC). Each incoming product seizes some resources, is processed by a machine, conveyed, and releases the resources. Cost accumulated by a product is broken down into several categories for analysis and optimization.
In this case, we’re training an AI agent to learn a policy for choosing factory floor parameters with the goal of optimizing product cost. State is defined as the product arrival rate, the number of resources and their utilization, idle and busy costs, as well as process time, and the speed of the conveyor belt. Action is defined as setting the number of resources, process time and the speed to the conveyor. The goal is to reduce cost per product while maintaining a high overall throughput. Users need to describe these parameters to the AI agent using machine teaching, then upload the simulation model and start training. The AI agent will start by initially picking random values for the action, then assess if the changed state is getting closer to the defined goal. Based on this assessment, the agent will adjust actions and over time will reach the goals defined by the user. Depending on problem complexity, the agent may require anywhere from hundreds of thousands to millions of these iterations. Once the goal has been reached, the AI agent has learned to always choose the best possible parameters for any given state of the production process. Enterprises could use a customized version of this simulation model in connection with the Project Bonsai service to optimize their factory floor processes.
The Project Bonsai preview is now available. To get started, you can either access it directly or request engagement from an expert through this form. The model used in this example and more information can be found on the AnyLogic website.
To learn more, please join AnyLogic and our Microsoft team for a live webinar on July 28 showcasing how you can bring deep reinforcement learning to practical business applications in a series of concise and easy-to-follow steps. In this webinar, we’ll demonstrate how an AnyLogic model can be transformed into an RL-ready model and used as the training environment (simulator) in Project Bonsai.
Four years ago, I joined the startup Bonsai, which envisioned a new way of training AI agents. The idea was to enable subject matter experts to use their knowledge of a particular problem to teach the AI agent how to make decisions about it, or to create an optimal control policy. Bonsai chose reinforcement learning (RL) as the first AI category to support, as we believed it could enable new use cases for automation and create significant value for future customers.
Before then, reinforcement learning had mostly received attention for teaching AI agents how to play games like Pong and other Atari classics. Then, OpenAI enabled users with a library of example environments that could be used to learn more about RL and increase performance of the latest RL algorithms. Soon thereafter, examples of simple physics-based models were added, either as simple robotic systems or games that took advantage of built-in physics engines. At Bonsai, we accelerated that trend and focused on teaching AI agents how to become more intelligent controllers for advanced control problems where traditional approaches may have shortcomings.
With a vision of developing an AI toolchain that enables engineers to add intelligence to their existing and future systems, we started to take a broader view of what might be possible. This goes back to the question: What is a controller? Is a supply chain or any other business process a controller? If so, could we make these controllers more intelligent?
I found a simulation model of the Beer Distribution Game on AnyLogic’s cloud platform and connected it to our deep reinforcement learning service to see if we could teach an AI agent to learn a successful control policy for one of the standard models taught in business school when supply chains are covered. It worked! It easily beat our co-workers when playing the game in real time and enabled our sales team to sign our first supply chain customer.
Fast forward to May 2020. After being acquired by Microsoft in 2018, Bonsai recently launched as a fully integrated Azure service at Microsoft’s Build developers conference. Over the past two years, we have continued to invest in our partnership with AnyLogic, and have learned more about how to use multi-method models with a deep reinforcement learning service such as ours.
If you’re not familiar with RL, it’s based on the idea of framing problems as a Markov decision process in which an AI agent learns a control policy to always pick the best possible action for a given state of the system. Ideally this system is somewhat random and dynamic, which makes a reward-based learning approach superior compared with other traditional control theories. More details can be found here.
A simplistic factory floor model where cost associated with product processing is calculated and analyzed using activity-based costing (ABC). Each incoming product seizes some resources, is processed by a machine, conveyed, and releases the resources. Cost accumulated by a product is broken down into several categories for analysis and optimization.
In this case, we’re training an AI agent to learn a policy for choosing factory floor parameters with the goal of optimizing product cost. State is defined as the product arrival rate, the number of resources and their utilization, idle and busy costs, as well as process time, and the speed of the conveyor belt. Action is defined as setting the number of resources, process time and the speed to the conveyor. The goal is to reduce cost per product while maintaining a high overall throughput. Users need to describe these parameters to the AI agent using machine teaching, then upload the simulation model and start training. The AI agent will start by initially picking random values for the action, then assess if the changed state is getting closer to the defined goal. Based on this assessment, the agent will adjust actions and over time will reach the goals defined by the user. Depending on problem complexity, the agent may require anywhere from hundreds of thousands to millions of these iterations. Once the goal has been reached, the AI agent has learned to always choose the best possible parameters for any given state of the production process. Enterprises could use a customized version of this simulation model in connection with the Project Bonsai service to optimize their factory floor processes.
The Project Bonsai preview is now available. To get started, you can either access it directly or request engagement from an expert through this form. The model used in this example and more information can be found on the AnyLogic website.
To learn more, please join AnyLogic and our Microsoft team for a live webinar on July 28 showcasing how you can bring deep reinforcement learning to practical business applications in a series of concise and easy-to-follow steps. In this webinar, we’ll demonstrate how an AnyLogic model can be transformed into an RL-ready model and used as the training environment (simulator) in Project Bonsai.
