Agencies are getting savvier at using artificial intelligence as data comes into greater focus as marketing and information technology are becoming more entwined.
Some studies back this up. For example, 81 percent of marketing and IT leaders surveyed by data platform Lytics said their two departments will become more involved in marketing over the next five years, while 66% of marketers plan to integrate AI into their marketing stack.
Experts say the use of AI is increasing as ad targeting with first-party data has become even in more demand. AI can help automate some of those processes, from creative to segmentation and potentially help agencies optimize their ad spend by cutting down on tedious tasks.
“I believe the true power of these technologies and tools are not to replace creatives, but rather make us more efficient,” said Ben Williams, TBWA Worldwide global chief creative experience officer. “There will always be a need for and value in creative direction, human curation, human refinement of an idea and decision making in terms of what is right for the brand we’re working with.”
But organizations are still experimenting with AI as the space grows, using it in a range of ways from moderating content and brand safety to implementing it in their communications strategy and creative products.
Generating content and creativity
One of the key ways agencies are testing AI is in the creative process, using data points to drive content. With these insights, AI generators are able to create relevant content in minutes or even seconds. But this doesn’t replace the work of content creators, acknowledged Nadia Gonzalez, CMO of AI marketing firm Scibids.
“It instead gives [creative teams] a rich tool to use, ensuring more diverse content is seen at just the right time and place,” Gonzalez said. “With companies of all sizes using data science and AI-driven analytics, we’ll also see greater dynamism in things like pricing, personalization and recommendations.”
At creative consultancy Codelab303, founder Anthony Chavez said understanding their clients’ desires is the first step in knowing how to use AI for the organization. Besides using automation for time-intensive tasks, they are utilizing AI tools for producing writing, music and other visuals. The firm has worked with brands such as Ulta Beauty and Carvana.
“There are activities that machines can do much better than humans,” Chavez said. “Whether the objective is providing real-time pricing, streamlining sales bookings or automating content marketing, there is likely an AI candidate within every organization, and the question is more about revealing the role than the resource.”
Continue reading: https://digiday.com/marketing/how-agencies-are-using-ai-to-innovate-for-clients-and-work-faster/

AI copywriting support has been around for a few years with tools including Jasper AI, which uses language models to suggest content for everything from Facebook ads to blog posts. Now that an AI has created its first Cosmo cover, it’s pretty clear that AI art has arrived in the ad industry, along with the worry that it might be a threat to jobs—maybe even the sanctity of human creativity itself.
But it’s important to consider that a human artist, Karen X. Cheng, was at the helm of the Cosmo project, using OpenAI’s Dall·E 2 as a different kind of creative tool. Because without good creative guidance, the output isn’t that great—as in Dall·E 2 interpreting an “Ad Age magazine cover:”
To get a more creative result requires a lot of interplay and dancing together with concepts and variations, riffing as you would alongside a creative partner with an end result in mind.
In the near term, at least, AI isn’t here to take our jobs—it’s here to spark and multiply our ideas, make work easier and generate better results for clients in the process.
Computer-generated art goes back decades. In the 1960’s, programmer Harold Cohen developed AARON, a computer capable of creating basic black and white images.
Continue reading: https://adage.com/article/opinion/artificial-intelligence-and-creative-marketing-how-brands-and-agencies-should-experiment/2428376

In today’s data-driven economy, technology is front and centre, with data being an organisation’s most critical asset, giving it a competitive edge if used, harnessed, and leveraged properly. Data enables organisations to predict customer behaviour, informs and guides corporate strategy and can also help drive efficiencies within the business.
Over the years, modern enterprises have witnessed multiple technology shifts in their daily environments, having evolved from the mainframe era to the cloud-based server era, to the virtual era and then to integrated appliances. Now we are in an era of microservices, containers and software-as-a-service (SaaS), with the latter squarely outpacing traditional applications.
While these new ways of innovation have brought great benefits to organisations – enabling them to adapt, become more agile and transform – it has also brought a significant set of challenges. Many of these environments have particular solutions that manage and protect them, resulting in pockets of data being protected in very different ways. Ultimately, this creates silos of data within the environment, which are fragmented and very hard to manage.
Increased complexity
Managing a legacy environment with new evolutionary workloads coming into the ecosystem is complex and as complexity increases, so does the security risk. As the security surface continues to evolve, so does the possibility of a significant data breach. So, while organisations get the benefits of this technology evolution, it is very important that they are aware of the security challenges that could come with it.
Continue reading: https://www.engineeringnews.co.za/article/future-proofing-it-environments-with-intelligent-data-management-solutions-2022-09-08

Agility is critical for any business looking to grow and remain relevant in today’s complicated industry landscape. Being able to quickly respond and reliably deliver actionable insights is vital for businesses — especially with changing market conditions and increasing customer demands.
One of the biggest market shifts in the last few years has been the rise in complex data sets and the speed at which data teams must respond. Data teams have been getting bogged down and experiencing burnout at an alarming rate. A recent study showed that 50% of data professionals feel constant pressure and stress from dealing with inefficient data integration – and it’s causing burnout.
This burnout has exposed one of the main barriers to the scalable delivery of value from data: not being able to respond to change quickly and reliably. Thankfully, because of the rise in cloud technology, methodologies have become available across the board in response, such as DataOps, DevOps, DevSecOps and MLOps, to name a few. Due to these innovations, teams can operate more efficiently and collaboratively to address this constant market change.
Scalable Operations
Cross-functional methodologies including DataOps, DevOps and MLOps have exploded over the last few years as a way to extend beyond traditional IT, tap into unique business functions, and drive faster time to insights. These all refer to architecture and operating principles that enable quick and reliable iteration in their particular discipline. Without them, trying to unnaturally force speed can result in design compromises and technical debt.

 
(Good_Stock/Shutterstock)
It’s said that 93% of organizations agree more automation opportunities exist – businesses are just not innovating fast enough to jump on the opportunity. Businesses should be taking more advantage of tools to fuel this need for automation since doing so will allow them to gain a competitive advantage. However, at the enterprise level, businesses are tackling adoption roadblocks due to skepticism of results, budget restrictions and generating buy-in from senior leadership.
By working to combat these challenges, and adopting DataOps and other methodologies as working practices in daily business operations and functions, organizations can alleviate stress and decrease their turnover rate. In tandem, changing the status quo of how things are traditionally done, will allow organizations to get the insights faster that customers and the business desire.
Where Data Integration Fits Into the Puzzle
Data integration is a key component of providing organizations with a 360 degree view of their data. But, as noted before, inefficient data integration is a contributing factor to burnout. Organizations can fix this by investing in solutions that streamline tedious tasks – such as data migration and maintenance. The goal is to free up data users’ time so they can focus on the most impactful projects and get a better handle on the influx of data across their organization. Enter DataOps.
Continue reading: https://www.datanami.com/2022/09/07/how-dataops-strengthens-business-resilience-and-agility/

Data governance programs are getting more and more attention in the corporate world, especially in industries that rely heavily on big data. Many businesses rely on accurate and well-managed assets that include information technology, business, and confidential or personal data.
The number of data sets that employees, partners, vendors, and customers need to regularly access and use continues to grow exponentially. As more data enters the picture, companies are recognizing that having a plan to help them manage this data becomes necessary. As a result, data governance programs are being created and optimized for future business needs.
What is a data governance program?
A data governance program includes best practices, policies, and procedures that protect the confidentiality and integrity of a company’s data. This type of program establishes standards and procedures for capturing, storing, managing, analyzing and sharing business data throughout its lifecycle from creation through deletion. By defining these rules and guidelines through a data governance program, businesses reduce the risk of violating privacy laws while simultaneously increasing customer satisfaction.
Why are data governance programs necessary?
Data governance programs are necessary to ensure that all organizational data is controlled and optimized for security, accessibility, and proper usage. This type of program provides a framework that directs the roles and responsibilities of employees that regularly work with data.
Data governance programs address a business’s need to control and manage data, which serves a number of purposes beyond employee best practices: protection of a company’s intellectual property, compliance with legal requirements and the establishment of common security standards. Without data governance programs in place, data inconsistencies can lead to lost time and money as resources are spent trying to reconcile inaccurate data.
Data governance eliminates enterprise data silos by focusing on how data flows through an organization. Implementing policies across different departments can help improve the effectiveness of team collaboration while also increasing employee transparency and trust.
To set up a successful data governance program, companies need to identify their specific needs so they can create processes according to those needs. The foundation of any good data governance program starts with mapping out what information is being collected, where it is stored and how it’s shared.
Continue reading: https://www.techrepublic.com/article/data-governance-program/

Nearly everywhere you look in the enterprise, IT architectures are shifting. From the data center to the cloud to the edge to the Internet of Things (IoT) devices and sensors coming online, compute is moving closer to end-users. But these accelerated changes are more than just shifts in architectures, tools and technology. They are changes in the ways business gets done.
A host of statistics reinforce the enormous change that is coming to the IT industry. According to Ziff Davis’ 2021 State of IT report, 76% of businesses plan long-term IT changes. IDC estimates that investment in edge computing power will grow much faster than core computing power over the next five years, and worldwide spending on edge computing servers will account for 24.9% of total servers by 2025. GSMA estimates that the global IoT market will be worth more than $1.1 trillion in revenue by 2025.
These changes will disrupt business models in nearly every sector. Organizations that embrace change with an innovation mindset will be uniquely positioned to leverage actionable insights from their networks and tools, becoming more agile and, ultimately, better able to serve their customers.
The Coming Transformation
To understand where we’re going, it’s important to understand where we are now. In the current enterprise, businesses use and deploy various applications, storing the data in business-specific data silos. The applications, tooling and data pipelines are typically managed by specific business units for their own purposes (which can be admittedly narrow). When data is reported to executives, it is generated according to the specific needs of the business unit leaders and their KPIs.
Continue reading: https://www.forbes.com/sites/forbestechcouncil/2022/09/07/embracing-change-through-innovation/?sh=4c80b164e2f5

Technological advances are changing the face of every industry, and the world of sports is no different, with digital tools bringing novel ways of watching and playing games. IoT devices have been included in the National Football League since 2019, and their influence and applications are growing each year.
From helmet sensors to protect players from concussions to augmented reality (AR) filters to give viewers a more immersive experience, here are some of the IoT technologies set to take center stage in this year’s NFL season.
Sensor Technology
When it comes to athletics, advances in data tracking and sensor technology have proven groundbreaking in providing in-depth insight into player performance and contested plays. One example is placing a tiny sensor on the football in play, capable of tracking distance, velocity and acceleration to build a holistic set of metrics, which can then be used by game managers and fans alike to build a player profile. This year’s preseason games used footballs embedded with microchips to monitor and analyze placement and handling of the ball and build a data set to inform future games.
The same concept can be applied to tagging the players themselves, capturing data on their movements, speed and game participation, though it can also go as detailed as player aggression, capacity to throw under pressure, time taken to throw, and much more. This data can then be provided to broadcasters to display or to managers to help build game plays. 
Robotic Football
Robotic assistants are becoming increasingly prevalent on and off the field. This year the Green Bay Packers became the first NFL team to use the football-launching robot, dubbed Seeker, during practice. 
The robotic quarterback has a six-ball magazine that can fire out footballs in various directions in nine seconds and can be programmed to imitate the job of several different players, such as a quarterback, punter or kicker. Initially developed to provide a contactless means of practicing football during the pandemic, the motorized robot is capable of “kicking” at a speed of up to 75 mph and can push out 500 throws per hour. 
Continue reading: https://www.iotworldtoday.com/2022/09/07/6-ways-iot-is-transforming-the-nfl/

A new piece of stealthy Linux malware called Shikitega has been uncovered adopting a multi-stage infection chain to compromise endpoints and IoT devices and deposit additional payloads.
"An attacker can gain full control of the system, in addition to the cryptocurrency miner that will be executed and set to persist," AT&T Alien Labs said in a new report published Tuesday.
The findings add to a growing list of Linux malware that has been found in the wild in recent months, including BPFDoor, Symbiote, Syslogk, OrBit, and Lightning Framework.
Once deployed on a targeted host, the attack chain downloads and executes the Metasploit's "Mettle" meterpreter to maximize control, exploits vulnerabilities to elevate its privileges, adds persistence on the host via crontab, and ultimately launches a cryptocurrency miner on infected devices.
The exact method by which the initial compromise is achieved remains unknown as yet, but what makes Shikitega evasive is its ability to download next-stage payloads from a command-and-control (C2) server and execute them directly in memory.
Privilege escalation is achieved by means of exploiting CVE-2021-4034 (aka PwnKit) and CVE-2021-3493, enabling the adversary to abuse the elevated permissions to fetch and execute the final stage shell scripts with root privileges to establish persistence and deploy the Monero crypto miner.
Continue reading: https://thehackernews.com/2022/09/new-stealthy-shikitega-malware.html

Most efforts to close the gender gap in science, technology, engineering, and mathematics fields focus on hiring. But women also quit STEM jobs at higher rates than men, an exodus that only intensified as millions of women left the labor market at the height of the COVID-19 pandemic.
“If we keep letting women leave, we’re not going to end up with more gender diversity,” says Shelley Correll, a sociology professor at Stanford University and a professor of organizational behavior, by courtesy, at Stanford Graduate School of Business. “We could start by stopping the bleeding.”
Correll and sociology PhD student Julia Melinopen in new window found one way to do just that — through an online program that offered support for women starting off in STEM. In March 2020, a group of early-career women at a North American biotechnology firm began meeting with coaches and peers through a virtual platform. The six-month intervention focused on developing soft skills — interpersonal abilities such as negotiation, influencing coworkers, and strategic networking.
The study began just before COVID-related lockdowns went into effect. “Because of the widely known challenges with work during the pandemic, we were expecting a big decline [in soft skills] for people who weren’t in the program and stability for those in the program. Instead, we saw improvement for women in the program, and the amount of improvement for a short program like this was surprising to us.”
Continue reading: https://www.gsb.stanford.edu/insights/teaching-soft-skills-can-help-women-stay-science-tech-jobs

The engineers who build and manage AI systems are increasingly valuable to companies across industry sectors. Unsurprisingly, the demand for their services outstrips the supply. 
But what is the role of an AI engineer? What are the key qualifications for the role? What really makes a good one? And how can they be made — maybe even from current developers on staff — if not found? Alternatively, how can the functionality otherwise be filled?
What is the role of an artificial intelligence (AI) engineer?
An AI engineer develops, programs, trains and deploys AI models. With 86% of companies in a recent survey reporting that AI is becoming mainstream in their businesses, the AI engineer has become a central figure.
While a data scientist focuses on finding and extracting business insights and applicable data from large datasets, an AI engineer comes from an IT infrastructure background and is charged with developing the algorithms for an AI application and integrating the application into a company’s broader tech environment. An engineer focused on algorithms may also be known as a machine learning (ML) engineer. Someone who specializes in integrating AI applications with an organization’s other technology may be known as an AI architect. Additionally, a professional specifically focused on writing code might have the title of AI developer.
Because an important part of an AI engineer’s job is applying AI to real-world use cases, these workers must understand the problems their companies face and find ways that AI can help solve them. That often includes collaborating with other departments and teaching others about AI’s potential.
AI engineer salary and benefits
AI engineers are highly skilled. They face a wide-open job market and are well compensated. ZipRecruiter reports that the average salary of an AI engineer is upwards of $158,000 a year, with top earners offered as much as $288,000 annually. Many companies employing these professionals also offer attractive benefits for these positions. AI engineering is a reasonably future-proof career, as AI is only becoming increasingly important to everyday life. 
Continue reading: https://venturebeat.com/ai/artificial-intelligence-ai-engineer-learn-about-the-role-and-skills-needed-for-success/

Modernizing industries depend heavily on emerging technologies. These technologies, like artificial intelligence, are primarily impactful for the manufacturing, energy, and transportation sectors. Enterprises are being transformed into a digital environment with emerging technologies. Every time the phrase “technology” is used, something new is always being developed or put into use that could benefit organizations.
A few years ago, no one thought emerging technologies would soon take over our lives. The users’ quick development has impacted the business ecosystem in wants and expectations for real-time interaction on these applications. These technical advancements significantly impact how we respond to global concerns. These new technologies can improve people’s lives, alter the course of the international economy, and improve the quality of life for present and future generations.
WHAT IS ARTIFICIAL INTELLIGENCE?
Artificial intelligence is, generally speaking, the activity of creating computer systems that can make intelligent decisions based on context rather than direct input. Understanding that AI systems always act following programmed rules is crucial. Consider a computer playing chess. While many people today would not consider this to be artificial intelligence (AI), it certainly satisfies the description of a system with rules that make decisions and estimates probability depending on the opponent’s movements.
Today, AI is becoming more popular as capabilities get closer to resembling sentience. This predicament results from various trends, which are essential elements needed when businesses incorporate AI into their strategies.
Continue reading: https://dataconomy.com/2022/09/emerging-technologies-artificial-intelligence/

Artificial intelligence is in transition, both as a technology and in how it’s being used. Companies are increasingly bringing AI pilots out of the test labs and deploying them at scale, and some are seeing significant benefits as a result. Regardless of any uncertainty surrounding AI, ignoring its potential poses the risk that companies doing business the old way will go under.
For many organizations, however, deriving value from AI may be elusive. Their models might not be tuned. Their training data sets might not be big enough. Customers may be leery. There are also concerns about bias, ethics, and transparency. Pushing an AI initiative into production before it’s ready, or expanding an AI strategy beyond an initial phase before properly vetting its results can cost a company money, or worse, send it in a direction detrimental to the business.
So how do you know whether an AI project will transform or sabotage your company? Without hard ROI numbers, companies have to get creative with ways to know for certain. Here’s a look at how IT leaders and industry insiders gauge value of AI.
Mature vs. groundbreaking technologies
Measuring the business value of any initiative or technology isn’t always a linear calculation. AI is certainly no exception, especially when degrees of maturity and business potential are taken into consideration. Proven and predictive variables — like data mining, cost and training savings, investment and the ability to facilitate new uses — influence decisions when it comes to acceptable ROI, but putting a degree of trust in the technology, no matter how new or established, is essential.
Continue reading: https://www.cio.com/article/405620/measuring-the-business-impact-of-ai.html

Retailers may not think of themselves as being in the business of managing data, but in many ways, they are. No other industry has more direct access to firsthand information about its customers through their behavior—what they like and what they don’t like, what they need and when they need it, what makes them happy and what frustrates them, and more. While retail interactions are first and foremost about helping people access the goods they need and want, taking the next step to think about them in terms of what they can teach—what data they can provide—can open up a host of opportunities for retail businesses.
And once that data is collected, artificial intelligence can help retailers take practical next steps. From better predicting their inventory needs to managing and supporting their employees, retail businesses can improve their operations and their customers’ experience and, thereby, the bottom line. Here, 15 members of Forbes Technology Council share smart ways leaders of retail businesses should be using AI in their operations.
1. To Create A Seamless Buying Experience
The use of AI in a retail business (and in any business, for that matter) should be about improving the customer experience. If consumer choice and past purchasing behavior is matched to just the right product offering, it creates a seamless user (buying) experience, and both the retailer and the consumer win. - Jeff Richards, SnapNurse
2. To Lower Costs And Improve Margins
The benefits of AI in the area of predictive analytics are wide-ranging and potentially game-changing. In particular, AI-driven analytics embedded into operational processes around customer engagement, inventory management and capacity planning can drive significant improvements in the accuracy of predictions and more optimal use of resources, leading to lower costs and higher margins. - Andre Dykhno, Change Healthcare
Continue reading: https://www.forbes.com/sites/forbestechcouncil/2022/09/06/15-smart-ways-retail-businesses-should-be-using-ai/?sh=1587ab601724

One of the messiest and thorniest national security challenges is how to keep Australians safe from manipulative online content – now, and into the future. The matter cuts across departmental jurisdictions in a way few other national security issues do – taking in questions relating to freedom of speech, defamation law, commerce, defense and intelligence, to name just a few.
As the internet continues to evolve, reaching further into the way people live their daily lives, these challenges will only grow. The last three-decade history of the internet has so far seen two distinct phases. Web 1.0 saw the advent of stand-alone websites; these were the static read-only sites of the 1990s and 2000s.
Web 2.0 is the social media age that most of us still operate in – a world of user-generated content, connectivity, e-commerce and data gathering. This phase has been largely dominated by the big social media companies, who were once celebrated as champions of the Arab Spring and protectors of the public sphere, but whose global status started changing in 2016, after a dark side became clear.
In a shift known as the tech lash, the corporate technology giants were blamed for a range of social and political ills; from spreading abusive material and disinformation to fueling polarization and hate speech. Perhaps above all, they have been maligned for the vast power and profit they derive from hoovering up and monetizing user data.
Governments around the world have spent the last decade grappling with how to exert jurisdictional powers over the internet giants. The last 12 months have seen a range of policy responses – from the European Union’s sweeping new Digital Services Act to Australia’s Anti-Trolling Bill; from the US Platform Transparency and Accountability Act to crackdowns on internet companies in India.
Continue reading: https://www.lowyinstitute.org/the-interpreter/web3-coming-national-security-implications-too

As the cryptocurrency market continues to grow and evolve, it’s becoming increasingly important for businesses to have a fundamental understanding of the technology and its potential implications. While cryptocurrency is often associated with volatile prices and speculative investing, there are many real-world applications for businesses across a range of industries. From payments and banking to supply chain management, cryptocurrency is starting to make its way into the mainstream.
Today, we’ll tell you more about why your business needs to understand crypto and how business leaders can benefit from registering in a cryptocurrency course. Investing in a cryptocurrency course can help your business stay ahead of the curve and better understand this emerging technology’s opportunities.
Before we explore why your business must understand crypto, let’s do a quick overview of cryptocurrency and how it works.
What is Cryptocurrency?
Cryptocurrency is a digital or virtual asset that relies on cryptography to secure its transactions and control the creation of new units. Cryptocurrency is decentralized, meaning it isn’t subject to government or financial institution control. Bitcoin is the first and most well-known cryptocurrency. It was created in 2009 as a peer-to-peer electronic cash system. Cryptocurrencies are decentralized—this means they aren’t subject to government or financial institution control. It can also be used to buy goods and services.
Now that we have a basic understanding of cryptocurrency, let’s explore some of the reasons your business needs to understand this technology.
Here are 10 reasons why your business needs to understand cryptocurrency:
Cryptocurrency is becoming more mainstream
Cryptocurrency is no longer the preserve of early adopters and tech-savvy investors. In recent years, we’ve seen a growing interest in cryptocurrency from both individuals and institutions. This is due in part to the increasing awareness of cryptocurrency and its potential applications. As more people learn about cryptocurrency and its potential uses, we’re likely to see even more adoption in the mainstream.
Continue reading: https://techbullion.com/why-your-business-needs-to-understand-cryptocurrency/

1. What is a decentralized identity?
A decentralized identity is a self-owned, independent identity that enables trusted data exchange.
Decentralized identity is an emerging Web3 concept based on a trust framework for identity management. Such decentralized identity management includes an approach to identity and access administration that allows people to generate, manage and control their personally identifiable information (PII) without a centralized third party like a registry, identity provider or certification authority.
Considered to be private and sensitive data, PII refers to the body of information about specific individuals that directly or indirectly identifies them. Usually, it combines name, age, address, biometrics, citizenship, employment, credit card accounts, credit history, et cetera. In addition to PII, information that forms a decentralized digital identity includes data from online electronic devices, such as usernames and passwords, search history, buying history and others.
With a decentralized identity, users can control their own PII and provide only the information that is required to be verified. Decentralized identity management supports an identity trust framework where users, organizations and things interact with each other transparently and securely.
2. Why does decentralized identity matter?
A decentralized identity aims to give people official proof of identity and complete ownership and control over their identities in a secure and user-friendly way.
A verifiable proof of existence is often needed for citizens to access essential services like healthcare, banking and education. Unfortunately, according to Worldbank data, 1 billion people on our planet still do not have an official proof of identity. A considerable part of the population is in a precarious position, unable to vote, open a bank account, own property or find a job. The inability to obtain identification documents limits people's freedom.
What’s more, traditional centralized identification systems are insecure, fragmented and exclusionary. Centralized identity databases are at risk as they often become prime targets for hackers. From time to time, we hear about hacks and attacks on centralized identity solutions in which thousands and millions of customer records are being stolen from major retailers.
Continue reading: https://cointelegraph.com/explained/what-is-decentralized-identity-in-blockchain

Permissionless access to data is one of blockchain’s most prominent promises; the idea that anyone anywhere can access and make use of data whichever way they want without requiring the say-so of a centralized entity. That could be access to real-time transaction information to make investment decisions based on the moves of whales (the crypto industry’s term for large investors). In theory, all that’s needed is to plug into the blockchain protocol of interest by setting up a node—essentially a computer that runs the blockchain’s software.
To appreciate how disruptive permissionless access to data is, consider how gaining access to the real-time transaction flow of the largest stock investors would work. In the United States, for example, an exchange such as Nasdaq will need to give you (or a third-party data provider) access to such data. The exchange has the right to decide who receives access and who doesn’t—and at what cost.
With blockchain, no one gets to make that call. The barrier to entry here is limited to the cost (both monetary and non-monetary) of setting up a node.
However, running nodes isn’t the most efficient way for most businesses to access and use blockchain data—especially for legacy companies looking to enter the Web3 space, said Tom Tirman, the cofounder and CEO of Parsiq.
Parsiq is a blockchain data infrastructure startup.
“Consider a traditional investment data provider who wants to start offering crypto data,” Tirman said. “Their preference would be to have access to structured data that can be processed and presented to users without adding the extra operational and technical layer of running their own nodes.”
The added operational and technical layer that Tirman referenced multiplies if the service provider intends to provide data from more than one blockchain network. That’s where blockchain data service providers come in.
Continue reading: https://www.forbes.com/sites/mikeozanian/2022/07/18/juan-soto-contract-rejection-could-make-orioles-a-better-buy-than-nationals/?sh=11ca81d46978

If one technology trend could prove to be even more tectonic and enduring than cloud computing, it is the blockchain. While the cloud challenges how we build software and modifies how we operate businesses, blockchain technology potentially alters how we think about and process transactions, authentication, and more. Beyond serving as a foundation for cryptocurrency, blockchain could influence in a fundamental way how we propose and record agreements.
The revolutionary nature of blockchain and the cryptocurrencies it enables are much touted. When contemplating how current technology developments might play into the future, it’s tough to identify another development more likely to influence the shape of things to come. Blockchain may prove to be the most significant innovation since the internet.
So what is blockchain technology, and what makes it so potentially transformative?
The case for decentralized transactions
Building distributed software systems is hard. The core of this difficulty is the data: protecting it, making it available, storing it. Although much of the difficulty stems from human beings trying to cheat the system, there is also inherent objective difficulty in overcoming failures and maintaining data consistency (for example, see the CAP theorem). Any time data is sent or retrieved—be it a post about your lunch or check the balance of your bank account—it is subject to these hazards.
In the case of something important, like your bank account, the traditional way to make data secure and accurate is via a trusted agent such as a bank. The distributed version of banking was the result of grafting traditional financial management practices onto the internet. The bank was trusted to persist and retrieve our financial information.
Continue reading: https://www.infoworld.com/article/3653379/a-quick-guide-to-blockchain.html

Ever since I can remember, I have heard phrases such as: “Girls can’t do that.” “That’s a man’s job.” “Working mom? You’re neglecting your kids.”
Fast forward to today, and what about all those female steelworkers (Flash Dance aside)? How about the large contingency of female doctors? Did you miss the string of stories from your favorite news outlet about the big jump in female lawyers?
We are, or at least should be, far past identifying a person’s gender as part of their title, role or position in the corporate world, and for the most part, that’s the standard. We don’t put "female" in front of manager or "male" in front of associate. They are simply managers, directors, associates and vice presidents.
Except when it comes to CEO. Time and again, the woman who leads a company as its chief executive officer has the word “female” inserted before her title in media and generally in society.
I have led companies and organizations for well more than a decade. Through those years, I acknowledge that there have been times where its appropriate to identify women by their gender before identifying their role or title, especially as women in businesses move higher up the corporate ladder and succeed despite the challenges society imposes on them.
Continue reading: https://www.forbes.com/sites/forbesbusinesscouncil/2022/09/06/shes-a-ceo-not-a-female-ceo/?sh=4034051c4366

When we think of tech pioneers, names like Bill Gates, and Steve Jobs steal the stage. Women behind technological changes are often forgotten, and so are their efforts. However, we can’t deny their contribution to the sophisticated digital era we live in today. Women didn’t just start changing the world recently. They always did. Even decades ago when technology started evolving, women stood equal to their masculine counterparts. The technology sector is full of amazing female personalities who devised game-changing inventions and shifted human history with their spectacular ideas. Henceforth, Analytics Insight brings you the list of 10 of the most famous women in technology.
Ada Lovelace: World’s First Computer Programmer
The daughter of famous poet Lord Byron, Ada Lovelace was born in 1815 in London. She was homeschooled by her mother and several tutors. Ada was taught science and mathematics, which went in her favor as she is now known as an English mathematician and writer. Ada’s skills and interest in machines lead to a working relationship with Charles Babbage, the inventor of the Analytical Engine, a complicated device that was never actually created but resembled the elements of the modern computer. Ada is referred to as the ‘World’s first computer programmer.’ Alan Turning used Ada’s notes on Analytical Engine for his modern computer.
Grace Hopper: The Mother of Computing
Grace Hopper was born in 1906 in New York and died in 1992. She was an esteemed computer scientist and one of the first computer programmers to work on Harvard Mark I. Grace’s vision of what computer eventually led her to develop COBOL, an early programming language that is still in use. She published the first algorithm intended to be carried out by a computer.
Continue reading: https://www.analyticsinsight.net/top-10-women-who-laid-the-first-stone-in-technology/

The government should have used the jobs summit to pave the way for a more generous paid parental leave scheme to support female entrepreneurs and get more women into technology start-ups, says Rachel Yang, a partner at venture capital firm Giant Leap.
Ms Yang said women could be discouraged from moving into start-ups as employees or founders by what they saw as a lack of financial stability. Stronger government support through increasing paid parental leave to 26 weeks and making childcare cheaper would counter that, making the start-up sector a less risky career choice for women.
“The government has missed an opportunity to improve the paid parental leave scheme in its immediate initiatives,” she said. “Currently, our government-funded scheme is the second worst in the developed world, so why wouldn’t we try to catch up and do more to help close the gender pay gap?”
While increasing Commonwealth-funded paid parental leave from 18 to 26 weeks and bringing forward childcare subsidies gained support from unions, some independent MPs and advocacy groups such as The Parenthood at last week’s Jobs and Skills Summit, they were not one of the 36 immediate initiatives agreed to at the event.
“Start-ups are often so small that financially it’s challenging to actually support longer maternity and parental leave policies because there’s a financial burden,” Ms Yang said, adding that some start-ups run with just enough funding to operate for a year.
Continue reading: https://www.afr.com/technology/the-jobs-summit-s-missed-opportunities-to-get-more-women-into-tech-20220902-p5bey5

Only34% of the peopleemployed in the largest tech companies such as Amazon, Apple, Facebook, Google and Microsoft are women.  The good news is women can change that percentage for the better.
Here are 7 tips on how women can effectively pursue a career in tech:
Build your business skills
Make it a point to enhance your business skills. In other words, look for opportunities to grow your expertise in both business and tech.
Be sure to bulk up on the following skills:

• Coding
• Computer science
• Data science
• Math
• Statistics
• System design

Seek mentorship
There’s nothing wrong with asking for help, especially when it comes to pursuing a career in tech. In fact, women need all the support that they can get when pursuing tech. That’s why it’s important to seek mentors who have been in your shoes before. While seeking women mentors are ideal, don’t forget about the men. Chances are, you’ll find a male mentor that sympathizes with women finding a purpose in the male-dominate workforce.
Continue reading: https://www.fierceelectronics.com/electronics/7-tips-women-pursuing-career-tech-henry

The advantages of artificial intelligence are many and only growing. AI can quickly translate a passage of text — for example, this article —into whatever language you'd prefer to read. AI can easily sort through tremendous amounts of data, providing humans with organized information at the touch of a few keystrokes. It can aid in the diagnosis of cancers, beat a Go master, choose a movie you'd like and order a pizza for you to eat while you watch it.
What Does This Mean?
If you're looking for the value of AI, you need look no further than its skill at protein folding. An AI program called AlphaFold proved capable of predicting a protein's structure based on its amino acid sequence, something humans have struggled to do. This is no fancy biological party trick. Predicting the shape of proteins will help researchers better understand the molecular structure of cells and be a great help in drug discovery and development, benefiting us all.
AI is fast, efficient, and in many ways even lives up to the second half of its name: intelligent. Some experts predict that not too many years hence, AI will reach the holy grail of general AI; that is, it will no longer be limited to specific tasks, such as protein folding or text translation, but will be able to do pretty much anything human intelligence can do, a hypothetical moment often referred to as "the singularity." At that point, the possibilities of AI would be limitless, with the potential to help humans in ways we haven't even imagined yet, says Max Tegmark, physicist and machine-learning researcher at MIT.
Continue reading: https://www.discovermagazine.com/technology/the-pros-and-cons-of-artificial-intelligence

Among the major trends in technology is the rapid development of artificial intelligence and its wide range of applications. In addition to enhancing technological applications, artificial intelligence allows us to simulate and expand human intelligence. 
As a technology, artificial intelligence has emerged as a critical component of complementing the efforts of human information security teams. Humans cannot adequately protect the dynamic attack surface of an organization alone. This is why artificial intelligence is becoming increasingly critical to cybersecurity professionals in order to reduce breach risk and improve security posture. It provides analysis and threat identification that is incredibly useful. 
Cyber security has risen to become a national concern as threats concerning it now need to be taken more seriously. A wide variety of viewpoints have been expressed on the issue of cybercrime, with many people coming at it from diverse perspectives.
The threat of cyber-crimes has expanded beyond conventional criminal activity and has now posed a threat to the national security of all countries, including the most technologically advanced ones. Interestingly, cybercrime is not limited to a single sector but affects a wide range of industries. Among the nations targeted by cybercrime is Nigeria.
Continue reading: https://www.vanguardngr.com/2022/09/enhancing-nigerias-cyber-security-with-artificial-intelligence/

A typical day. You get up in the morning and an AI tells you that traffic to work is heavy this AM. You read your curated newsfeed where an AI has selected what news articles you may find interesting. Product and movie recommendations follow you online. These are the AIs that you see. Behind the scenes, AIs are able to evaluate your health, your work history, your credit rating, and more. Your smartwatch provides recommendations on everything from breathing to exercise - and as technology races forward - will know not just your heart rate but your blood sugar history. For every human, some of these are conveniences and some are privacy intrusions. This is where AI Ethics comes in.
The confluence of sensor technology, the internet, massive computational resources, and AI - have led to a world where companies may know more about you than your family and friends (and maybe even more than you know about yourself!). As an illustrative example - researchers at Mount Sinai discovered that COVID-19 can be detected by a smartwatch well before any test. The value of such innovation is clear, but the risk less so. AI Ethics is the field of determining how to use such technology responsibly. Hopefully, the above examples illustrated why everyone should care about AI Ethics. In the rest of this post, we describe in more detail what AI Ethics is and how you can be part of the human-wide conversation about Ethical AI.
What are the different aspects of Ethical AI?
AI Ethics encompasses many areas at the intersection of technology, privacy, and human values, just to name a few. Some areas are:

• How can humans trust an AI? AI Trust (frequently mentioned in the same breath as AI Bias) is the area of Ethics which focuses on the need for AIs that are fair. Humans need to be convinced that decisions made by an AI are “fair” and do not favor or disfavor some groups inappropriately. The problem is that fairness itself is a subjective concept that humans do not agree on. Where humans do not agree - it is not possible for a computer program to please all.
• AI, Privacy, and Human Data. Between the internet and the growth of sensors, monitoring devices are everywhere. The last decade of AI has demonstrated that personal data can be used for everything from recommending books to detecting diseases. But who has the right to say what is allowed and what is not? The conversation about AI and privacy has already begun, with laws in the GDPR and others introducing clauses that empower individuals to control how corporations use private data. Data marketplaces are emerging, driving the control (and monetization) of personal information from the companies to individuals.
• AI impact on our environment. As AI models become bigger and bigger, the amount of resources they consume also gets bigger. Studies have shown that just one training of a large language AI model consumes as much energy as five cars in their lifetime (and these models do not just train once - they retrain many many times). On the other hand, AI is showing promise in helping the environment, in everything from greenhouse gas emission detections to finding novel enzymes that can eat plastics.

Continue reading: https://www.forbes.com/sites/nishatalagala/2022/09/05/ai-ethics-why-you-should-care/?sh=679e93726542