Warehouse Automation is Creating Bigger Opportunities In Logistic Sector

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E-commerce businesses are becoming increasingly popular, especially after the Covid-19 pandemic. To meet the rising demand for e-commerce volumes, the e-commerce industry along with the logistic companies are shifting to automation.

There is a mutual growth between the eCommerce businesses and logistic industries, and it is a common trait.

Automation is nothing new for the logistic industry. Even the use of steam engines during the industrial revolution can be labelled as automation to a large extent.

However, with the advancement in technology, a new form of automation has emerged in the form of robotic pickers and packers.

Also, automation is being employed in different areas of the logistic industry. One such automation is warehousing automation which has extremely high potential, especially for logistic companies like VRL and DTDC.

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From Imperial College London to IIM Kozhikode, Top Institutes Offering Online Data Science, Machine Learning Courses

 

EXECUTIVE POST GRADUATE PROGRAMME IN DATA SCIENCE FROM IIIT BANGALORE



Candidates can enroll in a completely online postgraduate programme in data science from IIIT Bangalore. Candidates must have a bachelor’s degree with minimum 50 per cent marks to be eligible to apply for the course. It offers five unique specialisations including deep learning, business analytics, data engineering, natural language processing, and business intelligence/data analytics. The programme is for 12 months and will start from April 30. One can apply online through upGrad.

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Defy Trends Is Bringing Data Analytics To Crypto Investment

The field of crypto investment is fraught with difficulty. There has been an increasing number of crypto scams taking place and most investment is done in the context of media hype and emotional investment.

Even those who keep their funds safe and are immune to hype don’t make the most of what crypto and DeFi have to offer; they are typically not investing based on sound principles or reliable data.

This is where Defy Trends comes in. Recognizing that the market is in need of accurate analytics and a data-based framework for investment, the team behind Defy Trends has created an application that offers a means for responsible and informed decision-making.


Defy Trends Helps To Make Informed Investment Decisions

While fiat trading has a plethora of tools and analytics available to execute trades, this is not the case with cryptocurrencies. Defy Trends fills this void with an application that assigns each coin a score between 0-100. This is not an arbitrary assignment, but a score based on a number of metrics from reliable data sources.

Projects are also individually scored between 0 - 100 on 4 distinct areas: trading score, on-chain score, news score, and social score. So people looking to trade on a certain strategy can place increased emphasis on a given category.

At the very least, this kind of information will help to spot scam coins so users do not waste their funds. Projects without sufficient information are liable to score very low on the Defy Trends index, regardless of what influencers are saying on social media.

“Actionable insights and quality information” is a signature statement from Defy Trends. The information is presented in a user-friendly dashboard so that the investor is not overloaded with data.

Defy Trends is the most advanced set of data analytics on the market that looks at millions of pieces of data from social media, on-chain transactions, community groups, online forums, news, and other sources to produce actionable and digestible indicators.


Crypto Investment: A Maturing Field

Defy Trends does more than offer a tool for informed decision-making. They are building a wider ecosystem that offers rewards for research contributions as well as modules for study. Data analytics are only useful when each analytic is understood in the context of other information.

There is little use in a sea of metrics that the user cannot understand, and this is why it has to be neatly presented with a well-rounded score. Even so, educational content is needed for further clarification.

Defy Trends also provides an Ambassador program. This program empowers women to learn about new technologies and the resulting investment opportunities, so they can achieve their long-term financial goals. It also creates network opportunities so participants can learn more about crypto investment and long-term wealth preservation in a new Web3 era.

The platform further offers solutions for businesses that are looking to get involved in Web3 as well as enterprises that are looking for a set of analytical tools for crypto and digital asset investment opportunities.


Why Data Analytics Are Needed

The days of portfolio managers and legal advisors are, if not numbered, at least going to be completely changed and disrupted. Individuals and businesses alike will need to take more direct control of their short and long-term finances. Crypto investment offers a means to do this, but it’s certainly not automatic; people need to learn how to use the system to preserve wealth.

This requires serious attention to crypto security and continual education, as well as reliable analytics for sustainable investment. This is exactly what Defy Trends provides, with a tool that aims to promote financial freedom regardless of class, ethnicity, background, religion, or gender.

Those who make wealth accidentally never keep it for long. Those who make it systemically and mathematically are practically guaranteed to have more success.

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Festo and MassRobotics leading healthcare robotics innovation

The Festo-MassRobotics Healthcare Robotics Startup Catalyst program celebrates the milestones achieved by the program’s four selected global startups at the Healthcare Robotics Engineering Forum. Key life sciences and robotics speakers to lead the event.



The successful Healthcare Robotics Startup Catalyst program came to an end on April 7th, 2022. The concluding ceremony will be held at the Healthcare Robotics Engineering Forum, Boston Convention and Exhibition Center, on May 11, 2022. The event includes an impressive lineup of speakers: ​​Fady Saad, Co-founder & Vice President of Strategic Partnerships at MassRobotics; Alfons Riek, Vice President of Technology and Innovation at Festo; Kendalle Burlin O’Connell, President & Chief Operating Officer at MassBio; Kenn Turner, President and CEO at Mass Life Sciences Center; and Brian Johnson, President at MassMedic. All four selected startup companies, Kinarm (Canada), Assistive Technology Development Inc. (United States), Eureka Robotics (Singapore), and Bionomous (Switzerland ) will, in turn, promote their companies, along with their products and service offerings. They will also be demonstrating their technologies on the event’s expo floor.

In October 2021, MassRobotics, Festo, and other key players in healthcare robotics, launched a Startup Catalyst Program to advance healthcare robotics companies around the world, by providing the networking opportunities, guidance, and resources they need to grow and succeed. The aim of the program was to connect healthcare robotics startups with customers, investors, suppliers, marketing, and overall support. The program focused on startups in the areas of clinical care, public safety, laboratory, supply chain automation, out-of-hospital care, quality of life, as well as continuity of work and education, and training and support for healthcare professionals.

More than 30 companies applied from all over the world, and the selection committee invited four to join in the program. The participating startups completed impressive milestones:Eureka Robotics develops and commercializes cutting-edge robotics and artificial intelligence (AI) technologies to automate high-accuracy, high-agility tasks. Eureka is currently completing fundraising rounds in Japan through connections provided by program mentors. Eureka was introduced to MassRobotics partner, Mitsubishi Electric, and signed a global partnership with Mitsubishi as a platinum partner. The program helped the company’s leadership to explore attractive applications in surgical lenses manufacturing technology, which is an extension to its focus on traditional manufacturing.
Bionomous provides laboratory equipment to automate the screening, sorting, and pipetting of miniature biological entities for more ethical and faster research in life science. CEO Frank Bonnet reports that with the aid of the Catalyst Program, Bionomous was able to run a pilot program in the US, leading to the company’s first sales outside Europe. This convinced Bionomous to expand into the US market and set up offices in the MassRobotics space in Boston. Bonnet emphasized the importance of the program’s mentors, who connected them to key industry leaders to open possibilities for future partnerships.
Assistive Technology Development Inc. is an American startup dedicated to at-home physical therapy solutions that are operable at a low cost and always accessible to rural patients and those who need closer monitoring for recovery. The company came into the program with three goals: 1) begin its first pilot study in a clinical setting; 2) downsize the actuation unit to a wearable form, and 3) raise capital. CEO Todd Roberts reports that with help from the program, the company has completed the first two milestones and is making progress on the third. It will begin phase I of a pilot study with UCHealth, a not-for-profit health care system, headquartered in Aurora, Colorado, on April 25th, allowing the company to present preliminary results at the keynote event at the Healthcare Conference. The study will assess the early clinical efficacy and collect patient and clinician feedback. Assistive’s actuation unit has been downsized by 70%, from a large, wall-powered, benchtop system to a wearable, battery-powered system that will enable the company to complete the pilot. Finally, Assistive is in the process of raising capital and has begun diligence with two firms.
Kinarm uses robotic arms to provide an objective assessment method to identify, measure, and track cognitive motor or sensory impairments resulting from injury or disease. Kinarm worked with assigned mentors from the robotics ecosystem who provided introductions to industry leaders who responded with “jaw-dropping, you-can-do-that?” exclamations, reports ​​Anne Vivian-Scott, CEO. Vivian-Scott was also introduced to experienced healthcare robotics leaders who will collaboratively aid Kinarm as the company scales its solutions. Vivian-Scott adds, “What we gained was not specific knowledge that can be encoded into our product, but direction. Quite frankly, most other programs are not ‘sufficiently vested’ in the participant’s business/opportunity to be able to offer such feedback.”

“I am grateful to Festo’s pioneering work to support our efforts to find global disrupting applications and startups in such a human-care field like healthcare, including life science, biotech, and medical devices,” said Fady Saad of MassRobotics.


“I am impressed with the quality of applications we received, and the unique structure of the program that allowed us to select such innovative companies and match them with world-class advisors,” said Festo’s Alfons Riek. “Certainly, we are excited about the networking opportunities opened to these companies and to presenting them to the world as great examples of the power of utilizing robotics in healthcare.”

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How Fintech Companies Are Using AI, Machine Learning To Create Alternate Lending Score

 

The access to funds and credit takes an individual one step closer to realising his/her financial dreams. When such access is instant, one doesn’t have to wait in line, or for the time when his/her credit score would improve in order to be eligible for credit. It is a liberating experience that is good for the person as well as for the economy at large.

While traditional banking systems have usually shied away from lending to certain segments of the populace, thereby leaving a large population underserved and unserved, fintech companies have been able to bridge that gap by becoming an alternative source of credit. Fintechs have been able to underwrite a diverse customer base, one that lives in smaller towns, Tier-3 or Tier-4 cities of India, thereby extending the government’s mandate of financial inclusion.

One may well credit Artificial Intelligence and Machine Learning, which help in creating a favourable credit environment for a broader range of users, thus, providing means of an alternative lending score that doesn’t rely solely only on an individual’s bureau score, and thereby, easing their financial access.

The need to adapt to newer technologies and cater to a wide customer base with customised needs has become the need of the hour, with both traditional banking systems and fintech companies constantly innovating. The latter has successfully used AI-ML to design products suiting their customer’s evolving needs. In fact, machine learning has had a major impact in the lending sector by allowing for more accurate and faster decision-making through analysis of consumer data, usage trends, and patterns.

As such, Machine Learning (ML) falls under the realm of AI, where ML uses algorithms and statistical models to perform real-time analysis of vast data sets. Together, AI and ML help lending enterprises identify, sort, and make accurate decisions based on multiple data points, rapidly and simultaneously. The benefits of using such disruptive tech are many, such as faster KYC, prompt arrival at a credit score, swift detection of fraud and risk management, and lower costs.

Once a user is allocated credit, ML models can figure out any anomalies in the pattern of usage. Diverse micromodels may be used to analyse and predict creditworthiness or changes in risk. Some of these models are also self-reinforcing, for example, each time a user makes a payment, a model can identify where they stand in their credit cycle; whether they have paid on time or not. The ML model makes decisions based on a user’s payment history, like reducing the interest rate for people consistently paying on time. ML models also assist users to make informed financial choices.

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16 Essential Steps For Creating And Maintaining An Effective Machine Learning Model

The insights available through effective machine learning models can help businesses develop customer personas, clarify marketing efforts, improve the user experience for their products and services, and much more. However, none of that can happen if an ML model isn’t carefully and correctly set up from the beginning. A flawed ML model can produce misleading outputs that may lead to costly missteps.



Most of us are familiar with the concept of “garbage in, garbage out”—that is, we know it’s important to input quality data to get quality information out. But there’s more to developing a truly effective ML model than that. It’s important to understand what even the best ML models can—and can’t—do and to be aware that it’s far from a “fix it and forget it” process. Here, 16 members of Forbes Technology Council share essential steps in the creation and maintenance of an effective machine learning model.


1. Begin With Operational Leaders’ Insights


Operational leaders understand what’s working for their business. However, this business sense isn’t scalable or repeatable to drive impact. That’s where ML models excel. While creating models, companies should start with operational leaders’ insights and then build, test and deploy the model in production. However, the models must be built for actionability to make them fully effective.

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A Day in The Life of Robotics Engineer Madi Babaiasl

For as long as I can remember, I was always interested in science. I liked math and physics in high school. When I wanted to go to university, I wanted to choose a major that involved math and physics, and also could solve real-world problems. The marriage between these two is engineering. First, I chose electrical engineering as my major. However, I wanted to study something that I could actually see, so I went and worked in robotics, which is more tangible. I was really interested in that because I could solve numerous problems through that knowledge, including my father’s hand tremors.

I hold a bachelor’s degree in Electrical Engineering with a focus on control engineering, a master’s degree in Mechatronics Engineering, both from the University of Tabriz in Iran, and a Ph.D. in Mechanical Engineering with a focus on medical robotics from Washington State University. During my bachelor’s degree, I had several internships where I learned about instrumentation, controller programming, mechatronics, and different sensors and actuators used in various industries. I also did several volunteer projects that I am proud of, including service to SWE and the Institute of Electronic and Electrical Engineers (IEEE). I was an eMentor for the IEEE “TryEngineering Together” outreach program and worked with middle school students to familiarize them with the engineering design process, which was a valuable experience for me.

I became fascinated by medical robotics during my Master’s. During that time, my dad suffered from hand tremors. His job involved working with highly delicate electronics on computer motherboards. This required him to have stable hands. I thought we could develop a device that could stop these tremors. I started this project with my team. We developed a device that could suppress tremors through placing electromyography (EMG) electrodes on muscles and correcting the signals that caused the tremor. This project was really important for me since I wanted to help my dad overcome his tremors and be better at his job.

During my robotics career, I worked on a variety of projects that I believe impacted society in general. My engineering work during my master’s led to new designs in improving medical assist robots for those that suffer from strokes or Parkinson’s disease. My Ph.D. research developed a new method for steerable needle insertion, namely water-jet steerable needles. The steerable needle can turn inside the patient and get to difficult-to-reach places in the body to administer drugs or perform medical operations.  In addition, I was able to solve a fundamental physics problem of how soft tissue interacts with waterjet cutting. My research and robotics work led to several journal and conference articles, accumulating more than 230 citations from the scientific community and a patent.

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Driving successful AI transformations at the enterprise level

Chandramauli Chaudhuri leads the Data Science initiatives across Fractal’s

Tech Media & Telecom vertical in the UK & Europe. He works in close

collaboration with senior business stakeholders and CXO teams across

some of the leading global enterprises, enabling the development of long-term strategic AI solutions.

Being in the field of Artificial Intelligence and Machine Learning for close to a decade and working across a wide range of industries, his primary area of interest lies in R&D, algorithmic customisation, capability enhancement, and MLOps deployments of solutions. Analytics India Magazine interviewed Chandramauli to gain insights into AI transformation at the enterprise level.

As a business leader driving AI transformation across an organisation, it is critical to understand that Artificial Intelligence is just the means of value realisation and not an end goal by itself. Thus, the factors differentiating success and failure lie in its synergy with the company’s core principles, value proposition and customer-centricity. AI adoption is not a plug-and-play solution that yields overnight returns. Businesses need to think beyond just the cutting-edge software, high-end infrastructure and skilled coders. Alignment of the company’s culture, customer expectations and ways of working to support such transformations need to take equal if not greater importance. The companies that are doing well, especially in banking, finance, media, telecom, and tech, are those that have integrated AI into their day-to-day functions. They are moving it away from being a siloed and ‘specialised’ initiative undertaken in small pockets, to broader cross-functional collaboration.

As far as emerging trends are concerned, organisations have started focusing a lot more on two key areas – execution excellence and risk management. This means nurturing an agile mindset across teams, pursuing the right use cases, developing a strong data foundation, investing in the right skills, and having a robust strategic roadmap. There has also been growing acknowledgement of the challenges associated with cybersecurity, user privacy, and digital consent. Issues like lack of explanations, absence of audit trails and presence of bias in AI systems have gained far greater prominence from the global community in the last couple of years than in the past decade. It’s true that we still have a long way to go and yet to fully appreciate the complex socio-political and economic implications. However, we have started looking in the right direction, focusing on building greater transparency and trust. The early adopters of these practices stand to reap the rewards in both the short and the longer term.

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WHY SYNTHETIC DATA AND DEEPFAKES ARE THE FUTURE OF DATA ANALYTICS?

What is synthetic data?

Synthetic data is data that you can create at any scale, whenever and wherever you need it. Crucially, synthetic data mirrors the balance and composition of real data, making it ideal for fueling machine learning models.

What makes synthetic data special is that data scientists, developers, and engineers are in complete control. There’s no need to put your faith in unreliable, incomplete data, or struggle to find enough data for machine learning at the scale you need. Just create it for yourself.

What is Deepfake?

Deepfake technology is used in synthetic media to create falsified content, replace or synthesizing faces, and speech, and manipulate emotions. It is used to digitally imitate an action by a person that he or she did not commit.

Advantages of deepfakes:

Bringing Back the Loved Ones!

Deepfakes have a lot of potential users in the movie industry. You can bring back a decedent actor or actress. It can be debated from an ethical perspective, but it is possible and super easy if we do not think about ethics! And also, probably way cheaper than other options.


Chance of Getting Education from its Masters

Just imagine a world where you can get physics classes from Albert Einstein anytime, anywhere! Deepfake makes impossible things possible. Learning topics from its masters is a way motivational tool. You can increase the efficiency, but it still has a very long way to go.

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