Connect with us

Politics

What’s Next? Machine Learning 2021 – ReadWrite

Published

on

What’s Next? Machine Learning 2021 - ReadWrite


The time for self-driving cars is already here. A permit was awarded to Nuro — the state’s first commercial permit for self-driving cars — from California’s Department of Motor Vehicles (DMV) in late December 2020.

This permit allows it to operate autonomous vehicles commercially on the roads of two counties. Welcome to the world of Artificial Intelligence and Machine Learning, wherein soon everything shall be autonomous and automated.

What’s Next? Machine Learning 2021

As per current reports, 65% of companies who are planning to adopt machine learning say the technology helps businesses in decision-making. In the article, we shall help you further understand and analyze these developments.

What is Machine Learning?

The current big data technology developments are churning out eons of data every second. But, what exactly should be done of this data if it cannot be well utilized well. Machine Learning ensures that the data patterns and processes thus created are utilized well to “train” machines as to how things need to be done.

Humans have forever tried to develop machines that could understand and analyze facts like humans and make decisions on their own, just like a human brain.

Under the purview of Artificial Intelligence, concepts and algorithms that are actually making machines smart enough to make autonomous decisions are called Machine Learning.

So, if an autonomous car decided to lower its speed in the forthcoming times, it is a Machine Learning led decision.

Trends that shall define the evolution of ML in 2021

Machine Learning makes a machine “smart.” With various applications and trending innovations in this circuit, there a plethora of developments in terms of businesses as well as products and services that shall be on offer for the users in 2021:

User Recommendations

Have you ever noticed the insightful and customized recommendations that Netflix offers its users as per their current “watchlist?”

In fact, it is now one of the most effective ways for the platform’s content creators to get found. Even the Amazon recommendations based on your earlier choices and orders are Machine Learning initiated.

With user experience topping the requirement list of all online businesses, 2021 is sure to witness several developments on these lines with more complex and thorough usabilities.

Image Recognition

Do you know about Google Lens and its various ML algorithms? The platform basically transforms machine-created images into virtual search options, leading the user to search for the related information online.

It is the best application development framework and basically involves image-based search rather than regular text-based searches. Lens uses computer vision, machine learning, and Google’s Knowledge Graph to make things work.

Mobile Apps like Facebook and Instagram also utilize similar algorithms to help users auto-tag their friends. Already a rage in the online community, the developments in this field are further touted to get more advanced in the upcoming times.

Voice Searches

More than half of all smartphone users have engaged with voice technology on their device in one form or the other. It is the future of how the world searches.

In-home voice-based searches through Alexa and Google-home have been transforming the complete user experience of varied connected devices as well. Further developments on these technologies include more streamlined conversations (without wake words like ‘ALEXA’ or ‘GOOGLE’) using evolved Machine learning-based NLP (Natural Language Processing).

There are algorithms, as well, as better compatibility and integrations within various connected devices and software. These developments are further set to evolve in 2021.

The ever-evolving Chatbots

Chatbots have been deployed to care for the customer relation management and HR verticals of businesses (especially in this COVID-19 era) with aplomb.

They are the new technology tool helping clients digital assets like websites, mobile apps, etc., to communicate with the users without any time-lapse. Basically, chatbots are of 2 kinds. The basic ones pick up trending keywords and provide viewers with answers already fed in the system.

However, the modern chatbots are of the second type wherein AI, and Machine Learning algorithms are being utilized to make them smart by helping them understand user requirements through the data they input.

With machine learning chatbots continuing to advance in 2021 as well, we are entering an age of intelligent automated shopping assistants that will make the overall experience smarter, to say the least.

Machine Learning and IoT devices

As you likely know, you can connect your Dyson to Alexa and control it. You can work to gain the same connectivity within the varied range of connected devices all around us. The list of such devices includes smartwatches, smart refrigerators, smart clothes, to name a few.

Reports suggest that the IoT market revenue is $212 billion worldwide. By 2025, there are expected to be more than 75 billion devices globally. Slowly, but gradually the systems monitoring and controlling them are touted to get smarter with more and more integration of ML-based algorithms.

The integration of these two technologies shall fire on the base platform to develop smart cities of the future. The concept and its related applications are already under development and are sure to come under real-time usage in many forms in 2021.

The culmination of these technologies shall enable the development of various smart new application ideas in the form of startups as well.

The technologies have also been playing quite a pivotal role in IIoT developments. IoT predicts the time at which a system or component will no longer perform its intended duties. ML can be effectively utilized in machine prognostics to end function, helping businesses predict machine issues, breakdowns, etc., leading to increased efficiency.

Machine Learning is now the choicest platform for Business Growth

A report by Crunchbase says that “Artificial Intelligence (A.I.) and machine learning (ML) related companies received a record $27.6 billion in funding in 2020.”

The trend is further set to evolve and expand in 2021, with more and more companies taking up the challenge to develop smarter gadgets and systems for more autonomous work and lifestyle.

These trends are sure to take a prominent part in these developments.

Image Credit: yan krukov; pexels; thank you!

Andrea Laura

Andrea Laura is a very creative writer and active contributor who love to share informative news or updates on various topics and brings great information to her readers. Being writing as her hobby, Andrea has come out with many interesting topics and information that attracts readers to unravel her write-up. Her content is featured on many mainstream sites & blogs.

Politics

Fintech Kennek raises $12.5M seed round to digitize lending

Published

on

Google eyed for $2 billion Anthropic deal after major Amazon play


London-based fintech startup Kennek has raised $12.5 million in seed funding to expand its lending operating system.

According to an Oct. 10 tech.eu report, the round was led by HV Capital and included participation from Dutch Founders Fund, AlbionVC, FFVC, Plug & Play Ventures, and Syndicate One. Kennek offers software-as-a-service tools to help non-bank lenders streamline their operations using open banking, open finance, and payments.

The platform aims to automate time-consuming manual tasks and consolidate fragmented data to simplify lending. Xavier De Pauw, founder of Kennek said:

“Until kennek, lenders had to devote countless hours to menial operational tasks and deal with jumbled and hard-coded data – which makes every other part of lending a headache. As former lenders ourselves, we lived and breathed these frustrations, and built kennek to make them a thing of the past.”

The company said the latest funding round was oversubscribed and closed quickly despite the challenging fundraising environment. The new capital will be used to expand Kennek’s engineering team and strengthen its market position in the UK while exploring expansion into other European markets. Barbod Namini, Partner at lead investor HV Capital, commented on the investment:

“Kennek has developed an ambitious and genuinely unique proposition which we think can be the foundation of the entire alternative lending space. […] It is a complicated market and a solution that brings together all information and stakeholders onto a single platform is highly compelling for both lenders & the ecosystem as a whole.”

The fintech lending space has grown rapidly in recent years, but many lenders still rely on legacy systems and manual processes that limit efficiency and scalability. Kennek aims to leverage open banking and data integration to provide lenders with a more streamlined, automated lending experience.

The seed funding will allow the London-based startup to continue developing its platform and expanding its team to meet demand from non-bank lenders looking to digitize operations. Kennek’s focus on the UK and Europe also comes amid rising adoption of open banking and open finance in the regions.

Featured Image Credit: Photo from Kennek.io; Thank you!

Radek Zielinski

Radek Zielinski is an experienced technology and financial journalist with a passion for cybersecurity and futurology.

Continue Reading

Politics

Fortune 500’s race for generative AI breakthroughs

Published

on

Deanna Ritchie


As excitement around generative AI grows, Fortune 500 companies, including Goldman Sachs, are carefully examining the possible applications of this technology. A recent survey of U.S. executives indicated that 60% believe generative AI will substantially impact their businesses in the long term. However, they anticipate a one to two-year timeframe before implementing their initial solutions. This optimism stems from the potential of generative AI to revolutionize various aspects of businesses, from enhancing customer experiences to optimizing internal processes. In the short term, companies will likely focus on pilot projects and experimentation, gradually integrating generative AI into their operations as they witness its positive influence on efficiency and profitability.

Goldman Sachs’ Cautious Approach to Implementing Generative AI

In a recent interview, Goldman Sachs CIO Marco Argenti revealed that the firm has not yet implemented any generative AI use cases. Instead, the company focuses on experimentation and setting high standards before adopting the technology. Argenti recognized the desire for outcomes in areas like developer and operational efficiency but emphasized ensuring precision before putting experimental AI use cases into production.

According to Argenti, striking the right balance between driving innovation and maintaining accuracy is crucial for successfully integrating generative AI within the firm. Goldman Sachs intends to continue exploring this emerging technology’s potential benefits and applications while diligently assessing risks to ensure it meets the company’s stringent quality standards.

One possible application for Goldman Sachs is in software development, where the company has observed a 20-40% productivity increase during its trials. The goal is for 1,000 developers to utilize generative AI tools by year’s end. However, Argenti emphasized that a well-defined expectation of return on investment is necessary before fully integrating generative AI into production.

To achieve this, the company plans to implement a systematic and strategic approach to adopting generative AI, ensuring that it complements and enhances the skills of its developers. Additionally, Goldman Sachs intends to evaluate the long-term impact of generative AI on their software development processes and the overall quality of the applications being developed.

Goldman Sachs’ approach to AI implementation goes beyond merely executing models. The firm has created a platform encompassing technical, legal, and compliance assessments to filter out improper content and keep track of all interactions. This comprehensive system ensures seamless integration of artificial intelligence in operations while adhering to regulatory standards and maintaining client confidentiality. Moreover, the platform continuously improves and adapts its algorithms, allowing Goldman Sachs to stay at the forefront of technology and offer its clients the most efficient and secure services.

Featured Image Credit: Photo by Google DeepMind; Pexels; Thank you!

Deanna Ritchie

Managing Editor at ReadWrite

Deanna is the Managing Editor at ReadWrite. Previously she worked as the Editor in Chief for Startup Grind and has over 20+ years of experience in content management and content development.

Continue Reading

Politics

UK seizes web3 opportunity simplifying crypto regulations

Published

on

Deanna Ritchie


As Web3 companies increasingly consider leaving the United States due to regulatory ambiguity, the United Kingdom must simplify its cryptocurrency regulations to attract these businesses. The conservative think tank Policy Exchange recently released a report detailing ten suggestions for improving Web3 regulation in the country. Among the recommendations are reducing liability for token holders in decentralized autonomous organizations (DAOs) and encouraging the Financial Conduct Authority (FCA) to adopt alternative Know Your Customer (KYC) methodologies, such as digital identities and blockchain analytics tools. These suggestions aim to position the UK as a hub for Web3 innovation and attract blockchain-based businesses looking for a more conducive regulatory environment.

Streamlining Cryptocurrency Regulations for Innovation

To make it easier for emerging Web3 companies to navigate existing legal frameworks and contribute to the UK’s digital economy growth, the government must streamline cryptocurrency regulations and adopt forward-looking approaches. By making the regulatory landscape clear and straightforward, the UK can create an environment that fosters innovation, growth, and competitiveness in the global fintech industry.

The Policy Exchange report also recommends not weakening self-hosted wallets or treating proof-of-stake (PoS) services as financial services. This approach aims to protect the fundamental principles of decentralization and user autonomy while strongly emphasizing security and regulatory compliance. By doing so, the UK can nurture an environment that encourages innovation and the continued growth of blockchain technology.

Despite recent strict measures by UK authorities, such as His Majesty’s Treasury and the FCA, toward the digital assets sector, the proposed changes in the Policy Exchange report strive to make the UK a more attractive location for Web3 enterprises. By adopting these suggestions, the UK can demonstrate its commitment to fostering innovation in the rapidly evolving blockchain and cryptocurrency industries while ensuring a robust and transparent regulatory environment.

The ongoing uncertainty surrounding cryptocurrency regulations in various countries has prompted Web3 companies to explore alternative jurisdictions with more precise legal frameworks. As the United States grapples with regulatory ambiguity, the United Kingdom can position itself as a hub for Web3 innovation by simplifying and streamlining its cryptocurrency regulations.

Featured Image Credit: Photo by Jonathan Borba; Pexels; Thank you!

Deanna Ritchie

Managing Editor at ReadWrite

Deanna is the Managing Editor at ReadWrite. Previously she worked as the Editor in Chief for Startup Grind and has over 20+ years of experience in content management and content development.

Continue Reading

Copyright © 2021 Seminole Press.