Making neural networks available for energy consumption prediction
We created LSTEnergy, a Long-Term-Short-Memory energy forecasting model built using Blossom Sky and real-world smart meter data acquired in 2020. It is a time-series forecasting model that predicts future events using time-based previous data and is typically performed once every week per smart meter. It works by training it on a collection of past data and then attempting to predict future values using the 'smartmeter' dataset. The model is trained to learn a function that transfers a series of prior observations as input to an output observation, and is used to optimize particular processes with AI. Long Short-Term Memory (LSTM) is a form of recurrent neural network (RNN) that can learn long-term dependencies.
Navigating the EU Corporate Sustainability Reporting Directive
The European Union (EU) has recently taken a significant step towards creating a more sustainable and responsible business environment by introducing the new Corporate Sustainability Reporting Directive (CSRD). The directive replaces the existing Non-Financial Reporting Directive (NFRD) and will require large companies to report on their sustainability and social responsibility efforts in a more detailed and standardized way. The CSRD will cover a wide range of sustainability topics, including environmental impact, social responsibility, and governance, and apply to all types of companies in the next four years. This will enable stakeholders to compare the sustainability efforts of different companies and track progress over time, thereby creating a more competitive business environment. The CSRD is expected to provide investors and consumers with more accurate and reliable information, encourage companies to improve their sustainability efforts, and create a more sustainable and responsible business environment that benefits society as a whole. To prepare for the new directive, companies can contact companies like Datalitiks, an award-winning data-driven start-up company that leverages technology and data to help organisations understand their ESG priorities and track their sustainability efforts.
Learning from Bank Failures and the Importance of Data in the Banking Industry
The recent collapse of Silicon Valley Bank (SVB) has once again highlighted the critical role that data plays in the banking industry. As a California-based bank that serves the startup tech sector, SVB was well-positioned to benefit from the boom in the tech industry. However, poor investment decisions and a lack of data-driven decision-making ultimately led to the bank's downfall.
Banks that prioritize data-driven decision-making are better equipped to navigate the complex and ever-changing landscape of the financial industry. Data plays a crucial role in helping banks make informed decisions about risk management, lending, and investments. By leveraging data analytics, banks can gain insights into their customers' behaviors and preferences, which can help them to develop tailored products and services that meet their needs. They can also use data to optimize their internal processes and reduce costs.
At Data Science Malta, we understand the importance of data in the banking industry, and we are here to help banks harness the power of data to drive their business forward. Our team of data scientists and analysts can help banks to develop customized data solutions that meet their specific needs and objectives, and to leverage data to improve their decision-making processes, reduce risks, and increase profitability.
Enable digital transformation with IoT (Internet of Things)
In today’s digital age, the Internet of Things (IoT) is driving the digital revolution. This technology allows us to connect physical devices, such as computers, mobile devices, and wearables, to a network and control them remotely. It is helping businesses to transform the way they operate, from improved customer experiences to automation of processes.
Federated Learning is necessary to avoid bias in Generative AI
As artificial intelligence becomes more integrated into our daily lives, it's important to consider the impact it has on our society. To avoid discrimination and bias, the most promising solution is federated learning, which uses a decentralized network of devices to process data, rather than relying on a central database, data warehouse or data lake. This approach helps to reduce the risk of biased results and makes it possible for a diverse group of people to contribute and help address potential biases. Join us in exploring this exciting area and how it can help shape a better future for all of us.
Why is federated learning so crucial for AI?
Federated learning (FL) is critical in a company's digital transformation since it enables decentralized, privacy-preserving machine learning model training. FL enables businesses to train models on decentralized data from multiple sources, resulting in more robust, scalable, and accurate models. Furthermore, FL assists businesses in overcoming data privacy concerns by allowing models to be trained without sharing raw data, lowering the risk of sensitive information being exposed or misused. FL also reduces the need for centralized data storage, processing, and maintenance, which lowers costs and increases efficiency. Businesses can also use FL to stay ahead in the fast-paced digital world and meet the changing needs of their customers and stakeholders.
The Power of Data: How to Use Reports to Boost Your Business
While you may think of data reports as boring, tedious, and purely business-related, the fact of the matter is that these reports are important to your business growth and development. Your data shows you how your business has grown (or not grown) over time, and it’s important to keep an eye on your data because it highlights the areas in which your business might need improvement. For example, if you notice that your net revenue has decreased month after month, then you know that something needs to change in order to turn things around and get back on track.
Are You Wasting Money in the Cloud? Public cloud repatriation starting off in 2023
Public cloud displacement is a subject we don't discuss as often as we ought to. Many see relocating data and apps back from a public cloud provider to an enterprise data center as an admission that the initial decision to move the workloads to the cloud was a grave error. In my opinion, this is less of a failure than a hosting platform change depending on the current state of the economy. People frequently return to more conventional platforms because of the high expense of cloud computing. You surly remember the article from Dropbox (1), explaining why they left their public infrastructure and went to a private cloud approach.
Regulation-Compliant Data Processing
Today regulation-compliant data processing is a major challenge, driven by regulatory bodies across the world. In this blog post, we analyzed data transfer regulations from the perspective of GDPR and discussed key research challenges for including compliance aspects in federated data processing. Compliance is at the core of our blossom data platform. In the next blog post, we will discuss how Databloom's blossom data platform addresses some of the aforementioned challenges and ensures regulation-compliant data processing across multiple clouds, Geo-locations, and data platforms.
Modern data strategy: Data Mesh - should you adapt?
The truth is that not every company will be a good fit for the installation of a Data Mesh. The main target market for Data Mesh is larger businesses that deal with unpredictability and change in their environments and operations. This article explains what a data mesh is, what its fundamental components are, how data-driven enterprises benefit from them, and whether a data mesh is a good fit for you. Remember – if your organization's data needs are low and stable over time, a Data Mesh is undoubtedly a waste of money.
Control and monitor your equipment remotely with the IoT Smart Timer Solution.
Electricity monitoring, scheduling and control are increasingly key features in several industries. This has subsequently increased the need for reliable remote electricity management and monitoring. The latest telecom innovations for the Internet of Things come to the rescue through reliable, autonomous, remote electricity control and monitoring solutions. These solutions are in the form of ultra-low power consumption devices, longer signal range and cost-effective solutions for data transfer.
USING VIRTUAL & AUGMENTED REALITY TO EFFECTIVELY ENGAGE THE ELDERLY
The EU is funding a project called VARTES to develop educational examples of how AR and VR technology can be used to help seniors suffering from early dementia.
6 easy, yet effective SEO techniques to increase your website traffic in 2022
Struggling to take your website to the next step? Various approaches can assist you in making your website work efficiently and reach the desired target audiences. For your website to not get lost in complex keyword algorithms on Google, Search Engine Optimisation (SEO) techniques could be employed. In this article, we’ll be discussing six easy SEO techniques to increase your website traffic. This strategy can be split up into off-page- and on-page SEO to manage aspects of your website and to drive traffic from search engines. Both techniques should be considered and implemented to create maximum results and to drive your website in the right direction. Want to know more?
Read on to see what you can do to optimize and promote your website.
Cyber Phishing: Towards Safeguarding Your Digital Future
Would you open your attachment to claim the €1 million prize promised in your email message?
A study unit, about the Strategy of lasting Industry 4.0
One of the largest challenges of Industry 4.0 is to manage it. To set a vision, and lead an enterprise to a lasting and digitally-integrated future. Executives and leaders need to understand Industry 4.0, its potential, and its challenges in order to make this happen. This brief article introduces a study unit that provides this unique and valuable knowledge.