Now, if a malicious user edits a Wikipedia article at the right place and adds a reference footnote, they can trick Slack into rendering a link that doesn’t exist in the article. That link can later be edited to redirect the victim to a malicious website.

Watch out - sharing a Wikipedia link on Slack could be a serious security no-no

Researchers document the Wiki-Slack attack, a new technique that uses modified Wikipedia pages to target end users on Slack.

Attackers Can Use Modified Wikipedia Pages to Mount Redirection Attacks on Slack

New reports from Microsoft and eSentire highlight some of them in the area called attackers-in-the-middle, or AITM. It’s a variation on the general man-in-the-middle types of attacks and packs a potent punch when combined with automated phishing-as-a-service kits.

New and more sophisticated phishing techniques leverage a variety of malicious tactics

GITEX GLOBAL 2023 – eSentire, Inc., the Authority in Managed Detection and Response (MDR), today announced that Inspira Enterprise Inc, (Inspira), a leader in business outcome-based ...

Inspira Joins eSentire’s e3 Partner Ecosystem to Deliver Award-Winning Managed Detection and Response Services to Organizations Globally

GITEX GLOBAL 2023 – eSentire, Inc., the Authority in Managed Detection and Response (MDR), today announced that Inspira Enterprise Inc, (Inspira), a leader in business outcome-based cybersecurity solutions and digital transformation, has joined its CRN 5 ...

WATERLOO, Ontario & DUBAI, United Arab Emirates–(BUSINESS WIRE)–#BHUSA—GITEX GLOBAL 2023 – eSentire, Inc., the Authority in Managed Detection and Response (MDR), today announced that Inspira Enterprise Inc, (Inspira), a leader in business outcome ...

WATERLOO, Ontario & DUBAI, United Arab Emirates, October 18, 2023--(BUSINESS WIRE)--GITEX GLOBAL 2023 – eSentire, Inc., the Authority in Managed Detection and Response (MDR), today announced ...

Together, eSentire and Inspira will help customers anticipate, withstand, and recover from cyberattacks across their entire attack surface, whether on-premises or in the cloud. Benefits of adopting eSentire Managed Detection and Response include: ? Rapid time to value, with service onboarding in only 14 days on average

Inspira Joins eSentire's e3 Partner Ecosystem to Deliver Award-Winning Managed Detection and Response Services to Organizations Globally

eSentire

esentire

Why Cybersecurity Firms Should Stop Bragging

Nowadays, quite a few companies are banking on new technologies and taking on the risks that come with them. Blockchain is hyped up but expensive and precarious, mobile app development is easy to pull off but throws you into a highly competitive market, etc. There’s no shame in using trusted and effective technologies, making a choice in favor of things like Scala and its contemporaries. So to prove that Scala is a viable choice, let’s take a look at successful companies and startups using Scala for product development. How Six Tech Giants Use Scala Before we go step by step, let’s just quickly look at a general list of top companies using Scala: LinkedIn Twitter Netflix Tumblr Foursquare AirBnB Pretty impressive, right? Now, let’s see how they use it and why. LinkedIn This well-know networking site announced its use of Scala in 2015 with the introduction of LinkedIn Signal. Built on the shoulders of Scala and JRuby, the system was meant to be a social search application with unique algorithms. The on Scala put it pretty concisely themselves: “if you are simply going to write Java with Scala syntax then you are not getting your money's worth”. This is very true and its one of the reasons why LinkedIn’s Scala usage is different from all others. They’ve merged it with things like Sinatra, Voldemort, and Norbert to create a mutli-functional Swiss army knife that they can use for all aspects of development. company experts LinkedIn, like some other companies, has supposedly raised concerns internally about Scala being too complex. However, this is refuted by the very experts that use it. They offer up the key point: Scala is only difficult on the outside. When you get into it, it’s a very easy tool to wield and the results it delivers are nothing short of outstanding. Twitter We’ll be upfront and mention that Twitter doesn’t use Scala exclusively. They also take advantage of Ruby on Rails. However, the latter is pretty poor for long-term processes and large-scale caching. That’s where Scala steps in. According to a , they like Scala because it’s flexible and fast. This matters a lot when you’re working on a product as massive and with as many diverse features as Twitter has. They use offshoots and variations of Scala for everything including streaming, search, data transfers, and graphing data. Twitter engineer Scala for development wasn’t the first choice for the company as onboarding newbies can get tough with a language that multi-faceted. However, the initial time cost is made up in flexibility and subsequent ease of use. Twitter engineers have built up a collection of custom libraries and made current development more streamlined for themselves. As a fun aside, Twitter jokes that they probably employ half of the world’s Scala experts and the other half is likely academics or working at Foursquare. Now, the isn’t working for Foursquare or teaching at universities… So it seems like we’re a hidden treasure when it comes to Scala developers! SysGears team Netflix The streaming giant uses Scala for search algorithms, restful APIs (and stable too, occasionally), and recommendations. Now, we could debate how well those recommendations actually work but the company is clearly satisfied. There’s an hour-long talk on the specifics of with plenty of fascinating code examples. Scala use at Netflix Netflix borrows Groovy and Java code to rework it in Scala and add interactive elements to the service, which is part of what made it successful in the first place. For Netflix, Scala is a cornerstone upon which much of the online version of the service was built. Its capabilities for machine learning changed the way the whole architecture of Netflix existed. And Scala made the tech giant what it is today. So, yes, Scala for machine learning is a great topic in and of itself. Tumblr The service might be a laughing stock now after its multiple questionable choices in terms of user restrictions but, just a couple of years ago, Tumblr was a sprawling and popular social network. This kind of expansion from its roots of a modest microblogging platform was made possible with… You guessed it, Scala! The company used a mix of Redis, Kafka, Scala, and a few other tools to keep scalability high. In fact, it even made its own framework - , also based on Scala. It’s intended to boost performance and keep things simple, two of the key characteristics you need if you want a service that scales well to a huge audience. Colossus Interestingly, one of the factors that pushed Scala through at Tumblr was the availability of devs with Ruby and PHP know-how. That made onboarding easy and likely encouraged experimentation. Tumblr immediately took advantage of Finagle, a library made by Twitter (a great example of Scala usage extending beyond the company and lifting others). Once Scala was taken on, the service slowly migrated its internal operations to it, relying more and more on Scala to do the job. Their new JVM-centric methods laid the groundwork for Tumblr to retool their architecture and handle a major shift to Scala, kind of similar to Netflix’s internal structure. However, Tumblr used Scala for scalability and not machine learning, showcasing the versatility of the programming language yet again. Foursquare It’s not as easy to find data on how and why Foursquare uses Scala. Well, the why is simple - because it’s flexible and, according to , helps with automation and has a very expressive type system. That’s some great praise and it’s even been put to action in an unexpected way. official sources The above example of Foursquare using Scala type system is surely just one of the ways the company has utilized the programming language. However, the more interesting aspect of it is that Scala was seemingly a non-contested choice with a big stake put on it. This kind of reliance is a good sign for the language as a whole and its community. With the support from tech giants and startups (we’ll get to those soon) as well as developers like the , the art of Scala is spreading every day. SysGears team AirBnB AirBnB is a truly international service on a huge scale and the one thing that’s always going to be a problem for this kind of company is finances. Not a lack of them but rather the issue of reporting them correctly and tracking the cash flow. This is where Scala came in for AirBnB as they to use the language based on its fault tolerance, type system (there it is again!) and fast data processing. And it didn’t disappoint as the new pipeline scales horizontally, works for current products, and will scale well with future ones. decided The main reasons why Scala got its place under the sun in AirBnB’s architecture are these: Scaling without sacrificing performance Functional programming won over declarative programming Quicker runs (4-5 hours) A sprawling test framework This is what we’d call very smart usage of the language, something that relies on all benefits of Scala and does so with elegance. That’s the kind of approach SysGears likes to take and the kind of approach that enriches the language itself and the community around it. How Four Startups Use Scala These are the new groundbreaking ways to use Scala, championing the technology in today’s environment. eSentire Despite confirming that Scala is still seen as a pretty high entry barrier, this startup has been using the technology for a while. Their main reason to love the language is the way functional programming combines quality with dependability. No downtime and outages will be a problem when using Scala. At least, that’s what the eSentire team posits. Hiya Holding the line against spam that plagues mobile devices, Hiya is using Scala as its sword and shield. According to the startup’s founder Nodir Yuldashev, they’ve already made customer-facing apps as well as internal solutions and data platforms, all with the help of Scala. This versatile approach to Scala development for startups is what sets the company apart and proves the potential of the language for future use. AdColony This mobile advertising startup is reaching over a billion people using Scala-based data processing. And, according to the founder, they’re putting more and more stake into the language as it’s elegant, fast, and almost everybody who comes to the company is willing to learn the ropes. Nortal This Estonian startup uses Apache Spark to build machine learning algorithms (move over, Netflix!) The company prefers Scala thanks to its flexibility and compatibility with big data solutions, which are two of the top Scala benefits. If you’d like to join the list of companies using Scala to get quality, fault tolerance, and success - SysGears expertise is here for you. Come discuss your ideas and we’ll build a project together.

How Six Tech Giants and Four Startups Use Scala

Your software is excellent. So, what’s preventing your customers from knowing more about—and adopting—more of your software offerings? Cross-portfolio access to your software applications and features can help customers derive value from a greater number of your products. Yet, three common impediments may be in the way of getting customers to embrace the valuable features and services that you provide. 1. They Don’t Know About All You Offer. If you’ve used Microsoft Word for word processing, you’ve probably also tried Microsoft Excel for creating and editing spreadsheets, both part of Microsoft 365 (formerly the Microsoft Office Suite). Maybe you use Adobe Acrobat Pro and occasionally have tried to edit some photos in Adobe Photoshop; both applications are part of Adobe Creative Cloud. In each of these examples, you’ve explored the offerings within a software supplier’s portfolio. The need for users to explore the software they use from their preferred providers isn’t just limited to what’s available from these ubiquitous offerings. Software producers across a wide variety of industries—medical, payments, restaurant management, fintech, security, and many more—offer robust software suites and portfolios. They include a variety of applications; each application includes varied, evolving features. Customers may select to do business with a company for a particular application or function of that app. Those same customers are likely looking for other functionalities to support their business. Maybe the customer needs an advanced function that may be available in different versions. Maybe they require limited-time access (such as for seasonal or project-based needs) to a particular application or feature. Maybe they’re looking for a new app to meet a specific need. If they don’t know what you offer, they’ll look elsewhere. You’re missing out on business. 2. You Make It Difficult for Customers to Try New Things. You sold a perpetual license to a customer for your flagship application. Maybe that user loves it and is loyal to that product. When you release a new feature, is it available to that user? Or are they locked into a restrictive software license, such as a perpetual monetization model (for which they paid for unlimited use of a particular software version), perhaps meaning that they can only get that new great feature if they upgrade to a newer version? Do they require a full year’s subscription for the product they need for just two weeks? If your entitlement management process (how access to software, devices, systems, and content is administered) is overly restrictive, you may be undermining business growth. By restricting access to your software products, you’re inherently preventing the exploration and adoption of your product. You’re preventing customers from learning about and trying everything you offer. 3. Your Approach to Software Monetization Isn’t Flexible Enough to Match Capacity and Demand. Each of your customers rides the waves of busy seasons in their particular business. When things are hectic, their demand for your product may go up. Perhaps they need additional users to access your software. Perhaps they would like to access your software’s premium features. Perhaps they need an additional application in your portfolio. If you’re unable to deliver the capacity that they demand, you’re missing out on opportunities to sell your entire portfolio to that account. __Elastic access __is a flexible approach that can remedy this mismatch. Rather than providing a static leased licensing capacity, elastic access offers an agile approach to the delivery of flexible usage rights. This pay-per-use approach (using what is sometimes called “prepaid,” “flexible credits,” “metered tokens,” or “consumptive tokens”) is highly practical for products and services where fluctuating usage patterns are likely. Customers can exchange prepaid credits to access any offering within your portfolio. This approach provides usage rights that stretch to accommodate your customers’ need for sporadic periods of higher consumption, allowing them to pay for specifically what they need during seasonal peaks, for specific projects, or for short-term occasional use by a particular license holder. Not only does a customer gain access to the product they need, but it helps align the expense you charge with the value that customers receive from your products. With elastic access, every consumptive event is reflected in real time. You benefit from real-time, granular usage data. This provides rapid software usage insights that can help product managers see the results of changes to products, influencing product roadmap and pricing/packaging decisions, while also supporting cross-sell and upsell initiatives. A flexible approach can also help software companies expand into new markets by providing easy entry to offerings. Access to Your Entire Portfolio Benefits the Entire Business Customers want to buy software in ways that fit their needs. Instant scalability, streamlined procurement, cost optimization and cost allocation functionality, and the ability to try new offerings without committing to long-term subscriptions are all essential for many customers. When you provide these, it benefits your bottom line, supporting customer retention and recurring revenue. Reducing friction in the sales process is always good business. Your software is excellent. So, what’s preventing your customers from knowing more about—and adopting—more of your software offerings? Your software is excellent. So, what’s preventing your customers from knowing more about—and adopting—more of your software offerings? Cross-portfolio access to your software applications and features can help customers derive value from a greater number of your products. Yet, three common impediments may be in the way of getting customers to embrace the valuable features and services that you provide. 1. They Don’t Know About All You Offer. If you’ve used Microsoft Word for word processing, you’ve probably also tried Microsoft Excel for creating and editing spreadsheets, both part of Microsoft 365 (formerly the Microsoft Office Suite). Maybe you use Adobe Acrobat Pro and occasionally have tried to edit some photos in Adobe Photoshop; both applications are part of Adobe Creative Cloud. In each of these examples, you’ve explored the offerings within a software supplier’s portfolio. The need for users to explore the software they use from their preferred providers isn’t just limited to what’s available from these ubiquitous offerings. Software producers across a wide variety of industries—medical, payments, restaurant management, fintech, security, and many more—offer robust software suites and portfolios. They include a variety of applications; each application includes varied, evolving features. Customers may select to do business with a company for a particular application or function of that app. Those same customers are likely looking for other functionalities to support their business. Maybe the customer needs an advanced function that may be available in different versions. Maybe they require limited-time access (such as for seasonal or project-based needs) to a particular application or feature. Maybe they’re looking for a new app to meet a specific need. If they don’t know what you offer, they’ll look elsewhere. You’re missing out on business. 2. You Make It Difficult for Customers to Try New Things. You sold a perpetual license to a customer for your flagship application. Maybe that user loves it and is loyal to that product. When you release a new feature, is it available to that user? Or are they locked into a restrictive software license, such as a perpetual monetization model (for which they paid for unlimited use of a particular software version), perhaps meaning that they can only get that new great feature if they upgrade to a newer version? Do they require a full year’s subscription for the product they need for just two weeks? If your entitlement management process (how access to software, devices, systems, and content is administered) is overly restrictive, you may be undermining business growth. By restricting access to your software products, you’re inherently preventing the exploration and adoption of your product. You’re preventing customers from learning about and trying everything you offer. 3. Your Approach to Software Monetization Isn’t Flexible Enough to Match Capacity and Demand. Each of your customers rides the waves of busy seasons in their particular business. When things are hectic, their demand for your product may go up. Perhaps they need additional users to access your software. Perhaps they would like to access your software’s premium features. Perhaps they need an additional application in your portfolio. If you’re unable to deliver the capacity that they demand, you’re missing out on opportunities to sell your entire portfolio to that account. __ Elastic access __is a flexible approach that can remedy this mismatch. Rather than providing a static leased licensing capacity, elastic access offers an agile approach to the delivery of flexible usage rights. This pay-per-use approach (using what is sometimes called “prepaid,” “flexible credits,” “metered tokens,” or “consumptive tokens”) is highly practical for products and services where fluctuating usage patterns are likely. Elastic access Customers can exchange prepaid credits to access any offering within your portfolio. This approach provides usage rights that stretch to accommodate your customers’ need for sporadic periods of higher consumption, allowing them to pay for specifically what they need during seasonal peaks, for specific projects, or for short-term occasional use by a particular license holder. Not only does a customer gain access to the product they need, but it helps align the expense you charge with the value that customers receive from your products. With elastic access, every consumptive event is reflected in real time. You benefit from real-time, granular usage data. This provides rapid software usage insights that can help product managers see the results of changes to products, influencing product roadmap and pricing/packaging decisions, while also supporting cross-sell and upsell initiatives. A flexible approach can also help software companies expand into new markets by providing easy entry to offerings. Access to Your Entire Portfolio Benefits the Entire Business Customers want to buy software in ways that fit their needs. Instant scalability, streamlined procurement, cost optimization and cost allocation functionality, and the ability to try new offerings without committing to long-term subscriptions are all essential for many customers. When you provide these, it benefits your bottom line, supporting customer retention and recurring revenue. Reducing friction in the sales process is always good business.

Why Aren’t Customers Exploring Your Entire Software Portfolio?

The Cyber Resilience Act: A Field Guide for CTOs and CISOs

Programmable Bitcoin Is Here: A Turing-complete Bridgeless Bitcoin Execution Layer

Proqramlaşdırıla bilən Bitcoin Buradadır: Turing-tam Körpüsüz Bitkoin İcra Layeri

প্রোগ্রামেবল বিটকয়েন এখানে: একটি টুরিং-সম্পূর্ণ ব্রিজলেস বিটকয়েন এক্সিকিউশন লেয়ার

Το προγραμματιζόμενο Bitcoin είναι εδώ: Ένα επίπεδο εκτέλεσης Bitcoin πλήρες χωρίς γέφυρα Turing

El Bitcoin programable ya está aquí: una capa de ejecución de Bitcoin sin puentes y con tecnología Turing completa

ביטקוין ניתן לתכנות נמצא כאן: שכבת ביצוע ביטקוין ללא ברידג' של טיורינג

プログラム可能なビットコインが登場: チューリング完全なブリッジレスビットコイン実行レイヤー

Bitcoin Boleh Aturcara Ada Di Sini: Lapisan Pelaksanaan Bitcoin Tanpa Bridgeless Turing yang lengkap

Seeraar la Baran-garayn karo Waa Halkan: Lakabka Fulinta Seeraar ee Lakabka ah ee Turing-buuxsan

Programmerbar Bitcoin är här: Ett Turing-komplett Bridgeless Bitcoin Execution Layer

Bitcoin Inayoweza Kupangwa Ipo Hapa: Tabaka la Utekelezaji la Turing-kamili la Bridgeless Bitcoin

Википедиа барномарезишаванда дар ин ҷост: Қабати иҷрокунии биткоинҳои бепули Тюринг

Bitcoin leyi nga phurogiremiwaka Yi Laha: Leyara ya ku Endliwa ka Bitcoin leyi nga riki na Buloho leyi heleleke ya Turing

Table of Links Abstract and 1. Introduction 2 The Original GPT4All Model 2.1 Data Collection and Curation 2.2 Model Training, 2.3 Model Access and 2.4 Model Evaluation 3 From a Model to an Ecosystem 3.1 GPT4All-J: Repository Growth and the implications of the LLaMA License 3.2 GPT4All-Snoozy: the Emergence of the GPT4All Ecosystem 3.3 The Current State of GPT4All 4 The Future of GPT4All Limitations and References 2 The Original GPT4All Model 2.1 Data Collection and Curation To train the original GPT4All model, we collected roughly one million prompt-response pairs using the GPT-3.5-Turbo OpenAI API between March 20, 2023 and March 26th, 2023. In particular, we gathered GPT3.5-Turbo responses to prompts of three publicly available datasets: the unified chip2 subset of LAION OIG, a random sub-sample of Stackoverflow Questions, and a sub-sample of Bigscience/P3 (Sanh et al., 2021). Following the approach in Stanford Alpaca (Taori et al., 2023), an open source LLaMA variant that came just before GPT4All, we focused substantial effort on dataset curation. The collected dataset was loaded into Atlas (AI, 2023)—a visual interface for exploring and tagging massive unstructured datasets —for data curation. Using AtarXiv:2311.04931v1 [cs.CL] 6 Nov 2023 las, we identified and removed subsets of the data where GPT-3.5-Turbo refused to respond, had malformed output, or produced a very short response. This resulted in the removal of the entire Bigscience/P3 subset of our data, as many P3 prompts induced responses that were simply one word. After curation, we were left with a set of 437,605 prompt-response pairs, which we visualize in Figure 1a. This paper is available on arxiv under CC BY 4.0 DEED license. Authors:
(1) Yuvanesh Anand, Nomic AI, yuvanesh@nomic.ai;
(2) Zach Nussbaum, Nomic AI, zach@nomic.ai;
(3) Adam Treat, Nomic AI, adam@nomic.ai;
(4) Aaron Miller, Nomic AI, aaron@nomic.ai;
(5) Richard Guo, Nomic AI, richard@nomic.ai;
(6) Ben Schmidt, Nomic AI, ben@nomic.ai;
(7) GPT4All Community, Planet Earth;
(8) Brandon Duderstadt, Nomic AI, brandon@nomic.ai with Shared Senior Authorship;
(9) Andriy Mulyar, Nomic AI, andriy@nomic.ai with Shared Senior Authorship. Table of Links Abstract and 1. Introduction Abstract and 1. Introduction 2 The Original GPT4All Model 2 The Original GPT4All Model 2.1 Data Collection and Curation 2.2 Model Training, 2.3 Model Access and 2.4 Model Evaluation 2.2 Model Training, 2.3 Model Access and 2.4 Model Evaluation 3 From a Model to an Ecosystem 3.1 GPT4All-J: Repository Growth and the implications of the LLaMA License 3.1 GPT4All-J: Repository Growth and the implications of the LLaMA License 3.2 GPT4All-Snoozy: the Emergence of the GPT4All Ecosystem 3.2 GPT4All-Snoozy: the Emergence of the GPT4All Ecosystem 3.3 The Current State of GPT4All 3.3 The Current State of GPT4All 4 The Future of GPT4All 4 The Future of GPT4All Limitations and References Limitations and References 2 The Original GPT4All Model 2.1 Data Collection and Curation To train the original GPT4All model, we collected roughly one million prompt-response pairs using the GPT-3.5-Turbo OpenAI API between March 20, 2023 and March 26th, 2023. In particular, we gathered GPT3.5-Turbo responses to prompts of three publicly available datasets: the unified chip2 subset of LAION OIG, a random sub-sample of Stackoverflow Questions, and a sub-sample of Bigscience/P3 (Sanh et al., 2021). Following the approach in Stanford Alpaca (Taori et al., 2023), an open source LLaMA variant that came just before GPT4All, we focused substantial effort on dataset curation. The collected dataset was loaded into Atlas (AI, 2023)—a visual interface for exploring and tagging massive unstructured datasets —for data curation. Using AtarXiv:2311.04931v1 [cs.CL] 6 Nov 2023 las, we identified and removed subsets of the data where GPT-3.5-Turbo refused to respond, had malformed output, or produced a very short response. This resulted in the removal of the entire Bigscience/P3 subset of our data, as many P3 prompts induced responses that were simply one word. After curation, we were left with a set of 437,605 prompt-response pairs, which we visualize in Figure 1a. This paper is available on arxiv under CC BY 4.0 DEED license. This paper is available on arxiv under CC BY 4.0 DEED license. available on arxiv Authors: (1) Yuvanesh Anand, Nomic AI, yuvanesh@nomic.ai; (2) Zach Nussbaum, Nomic AI, zach@nomic.ai; (3) Adam Treat, Nomic AI, adam@nomic.ai; (4) Aaron Miller, Nomic AI, aaron@nomic.ai; (5) Richard Guo, Nomic AI, richard@nomic.ai; (6) Ben Schmidt, Nomic AI, ben@nomic.ai; (7) GPT4All Community, Planet Earth; (8) Brandon Duderstadt, Nomic AI, brandon@nomic.ai with Shared Senior Authorship; (9) Andriy Mulyar, Nomic AI, andriy@nomic.ai with Shared Senior Authorship. Authors: Authors: (1) Yuvanesh Anand, Nomic AI, yuvanesh@nomic.ai; (2) Zach Nussbaum, Nomic AI, zach@nomic.ai; (3) Adam Treat, Nomic AI, adam@nomic.ai; (4) Aaron Miller, Nomic AI, aaron@nomic.ai; (5) Richard Guo, Nomic AI, richard@nomic.ai; (6) Ben Schmidt, Nomic AI, ben@nomic.ai; (7) GPT4All Community, Planet Earth; (8) Brandon Duderstadt, Nomic AI, brandon@nomic.ai with Shared Senior Authorship; (9) Andriy Mulyar, Nomic AI, andriy@nomic.ai with Shared Senior Authorship.

Original GPT4All Model: How We Collected Data and Then Curated It

Authors:
(1) Hoon Kim, Beeble AI, and contributed equally to this work;
(2) Minje Jang, Beeble AI, and contributed equally to this work;
(3) Wonjun Yoon, Beeble AI, and contributed equally to this work;
(4) Jisoo Lee, Beeble AI, and contributed equally to this work;
(5) Donghyun Na, Beeble AI, and contributed equally to this work;
(6) Sanghyun Woo, New York University, and contributed equally to this work. Editor's Note: This is Part 7 of 14 of a study introducing a method for improving how light and shadows can be applied to human portraits in digital images. Read the rest below. Table of Links Abstract and 1. Introduction
2. Related Work
3. SwitchLight and 3.1. Preliminaries
3.2. Problem Formulation
3.3. Architecture
3.4. Objectives
4. Multi-Masked Autoencoder Pre-training
5. Data
6. Experiments
7. Conclusion Appendix A. Implementation Details
B. User Study Interface
C. Video Demonstration
D. Additional Qualitative Results & References 4. Multi-Masked Autoencoder Pre-training We introduce the Multi-Masked Autoencoder (MMAE), a self-supervised pre-training framework designed to enhance feature representations in relighting models. It aims to improve output quality without relying on additional, costly light stage data. Building upon the MAE framework [19], MMAE capitalizes on the inherent learning of crucial image features like structure, color, and texture, which are essential for relighting tasks. However, adapting MAE to our specific needs poses several non-trivial challenges. Firstly, MAE is primarily designed for vision transformers [15], while our focus is on a UNet, a convolution-based architecture. This convolutional structure, with its hierarchical nature and aggressive pooling, is known to simplify the MAE task, necessitating careful adaptation [50]. Further, the hyperparameters of MAE, particularly the fixed mask size and ratio, are also specific to vision transformers. These factors could introduce biases during training and hinder the model to recognize image features at various scales. Moreover, MAE relies solely on masked region reconstruction loss, limiting the model to understand the global coherence of the reconstructed region in relation to its visible context. To address these challenges effectively, we have developed two key strategies within the MMAE framework: Dynamic Masking. MMAE eliminates two key hyperparameters, mask size and ratio, by introducing a variety of mask types to generalize the MAE. These types, which include overlapping patches of various sizes, outpainting masks [46], and free-form masks [29] (see Fig.5), each contribute to the model’s versatility. With the ability to handle challenging masked regions, MMAE achieves a more comprehensive understanding of image properties. Generative Target. In addition to its structural advancements, MMAE incorporates a new loss function strategy. We have adopted perceptual [24] and adversarial losses [22], along with the original reconstruction loss. As a result, MMAE is equipped not only to reconstruct missing image parts but also to ensure synthesis capabilities and their seamless integration with the original context. In practice, the weights for the three losses are equally set. We pre-train the entire UNet architecture using MMAE, and, unlike MAE, we retain the decoder and fine-tune the entire model on relighting ground truths. This paper is available on arxiv under CC BY-NC-SA 4.0 DEED license. Authors: (1) Hoon Kim, Beeble AI, and contributed equally to this work; (2) Minje Jang, Beeble AI, and contributed equally to this work; (3) Wonjun Yoon, Beeble AI, and contributed equally to this work; (4) Jisoo Lee, Beeble AI, and contributed equally to this work; (5) Donghyun Na, Beeble AI, and contributed equally to this work; (6) Sanghyun Woo, New York University, and contributed equally to this work. Authors: Authors: (1) Hoon Kim, Beeble AI, and contributed equally to this work; (2) Minje Jang, Beeble AI, and contributed equally to this work; (3) Wonjun Yoon, Beeble AI, and contributed equally to this work; (4) Jisoo Lee, Beeble AI, and contributed equally to this work; (5) Donghyun Na, Beeble AI, and contributed equally to this work; (6) Sanghyun Woo, New York University, and contributed equally to this work. Editor's Note: This is Part 7 of 14 of a study introducing a method for improving how light and shadows can be applied to human portraits in digital images. Read the rest below. Editor's Note: This is Part 7 of 14 of a study introducing a method for improving how light and shadows can be applied to human portraits in digital images. Read the rest below. Editor's Note: This is Part 7 of 14 of a study introducing a method for improving how light and shadows can be applied to human portraits in digital images. Read the rest below. Editor's Note: This is Part 7 of 14 of a study introducing a method for improving how light and shadows can be applied to human portraits in digital images. Read the rest below. Table of Links Abstract and 1. Introduction 2. Related Work 3. SwitchLight and 3.1. Preliminaries 3.2. Problem Formulation 3.3. Architecture 3.4. Objectives 4. Multi-Masked Autoencoder Pre-training 5. Data 6. Experiments 7. Conclusion Abstract and 1. Introduction Abstract and 1. Introduction 2. Related Work 2. Related Work 3. SwitchLight and 3.1. Preliminaries 3. SwitchLight and 3.1. Preliminaries 3.2. Problem Formulation 3.2. Problem Formulation 3.3. Architecture 3.3. Architecture 3.4. Objectives 3.4. Objectives 4. Multi-Masked Autoencoder Pre-training 4. Multi-Masked Autoencoder Pre-training 5. Data 5. Data 6. Experiments 6. Experiments 7. Conclusion 7. Conclusion Appendix A. Implementation Details B. User Study Interface C. Video Demonstration D. Additional Qualitative Results & References A. Implementation Details A. Implementation Details B. User Study Interface B. User Study Interface C. Video Demonstration C. Video Demonstration D. Additional Qualitative Results & References D. Additional Qualitative Results & References 4. Multi-Masked Autoencoder Pre-training We introduce the Multi-Masked Autoencoder (MMAE), a self-supervised pre-training framework designed to enhance feature representations in relighting models. It aims to improve output quality without relying on additional, costly light stage data. Building upon the MAE framework [19], MMAE capitalizes on the inherent learning of crucial image features like structure, color, and texture, which are essential for relighting tasks. However, adapting MAE to our specific needs poses several non-trivial challenges. Firstly, MAE is primarily designed for vision transformers [15], while our focus is on a UNet, a convolution-based architecture. This convolutional structure, with its hierarchical nature and aggressive pooling, is known to simplify the MAE task, necessitating careful adaptation [50]. Further, the hyperparameters of MAE, particularly the fixed mask size and ratio, are also specific to vision transformers. These factors could introduce biases during training and hinder the model to recognize image features at various scales. Moreover, MAE relies solely on masked region reconstruction loss, limiting the model to understand the global coherence of the reconstructed region in relation to its visible context. To address these challenges effectively, we have developed two key strategies within the MMAE framework: Dynamic Masking. MMAE eliminates two key hyperparameters, mask size and ratio, by introducing a variety of mask types to generalize the MAE. These types, which include overlapping patches of various sizes, outpainting masks [46], and free-form masks [29] (see Fig.5), each contribute to the model’s versatility. With the ability to handle challenging masked regions, MMAE achieves a more comprehensive understanding of image properties. Dynamic Masking. Generative Target. In addition to its structural advancements, MMAE incorporates a new loss function strategy. We have adopted perceptual [24] and adversarial losses [22], along with the original reconstruction loss. As a result, MMAE is equipped not only to reconstruct missing image parts but also to ensure synthesis capabilities and their seamless integration with the original context. In practice, the weights for the three losses are equally set. Generative Target. We pre-train the entire UNet architecture using MMAE, and, unlike MAE, we retain the decoder and fine-tune the entire model on relighting ground truths. This paper is available on arxiv under CC BY-NC-SA 4.0 DEED license. This paper is available on arxiv under CC BY-NC-SA 4.0 DEED license. available on arxiv

AI Learns to Perfect Lighting in Photos Using Smart Masks and Creative Training

Holiday marketing, as it’s preached, is a con. A ritualized scam sold to startups by ad platforms, agencies, and marketers who profit from your desperation. Do you really think you can outspend Amazon, out-charm Coca-Cola, or outmaneuver Nike? Unless you’re secretly printing money in your garage, no. Christmas isn’t for playing Santa with jingles and 20% off codes—it’s for hunting a whale. Next year, turn your entire marketing strategy into a public obsession with one person. Not a “demographic market.” Not a target persona. A single, breathing, flesh-and-blood human being whose “yes”could grant you permanent access to Cuban’s Cabo cocktail club. Bet it all on a campaign so precise it’s borderline psychotic. Dangerous? Stupid? Obviously, and probably. But boring? Never. If it crashes, people will talk. If it flies, you’ll own the year. Either is better than begging the Internet for clicks, plus it’ll give you a great story (or a great excuse to drink). Holiday Marketing Sucks. This is a classic David vs. Goliath scenario—except Goliath has a machine gun and David forgot his slingshot. Here’s why it’s a losing battle: You’re Outgunned And Outclassed Every big brand with deep pockets is jacking up CPMs. Ad costs more than double, competition spikes, and algorithms prioritize whoever spends the most. Yeah, obviously not you. If your $10K campaign could talk, it would whisper: "Help." You’re Selling To Zombies By mid-December, your CTA is competing with drunken relatives, shipping delays, and 87 ads about the perfect gift for canine therapists. Your audience is fried and their brains are coasting on autopilot—barely capable of choosing between two brands of wrapping paper. You’re Competing With Santa Claus—Not Other Businesses Know why Apple kills it every Christmas? It’s not with Siri, but with sentiment. The holiday giants use their war chests to craft masterpieces that ride on the emotional meaning of the season—nostalgia, tradition, family values—and if you’re not on par, you come off like a door-to-door salesman in a Saint Nick suit. ROI = Regret On Investment December sales bring January sobs. Whatever you make from your festive push will be eaten alive by your CPA—and you’ll wake up next month drowning in remorse, invoices, and wondering where the cash went. (Hint: Zuck’s back pocket) Why Serenading One Person Is The Smartest Play The best presents don’t come in mass-produced packages. Neither should your holiday marketing. A custom campaign is as much a gift to them as it is to you. It’s Psychological Warfare People hate being sold to, but they love feeling chosen. Focusing on one person creates a psychological bind: If they respond, they know they’re winning because you’ve done all the work to court them.If they don’t respond, they wonder if someone else will—and if they’ll miss their shot. It’s The Ultimate Litmus Test For Your Product If you can’t convince one perfect-fit customer, how will you convince hundreds? A campaign por uno is the fastest way to figure out if your pitch, product, and strategy are sharp enough to scale. It’s The Best Marketing Boot Camp A one-person campaign is combat training. No crutches of generic strategies, no Canva, no “but our CTR was decent” excuses—survival here relies on raw ingenuity, superhuman agility, and uncompromising precision. Success isn’t guaranteed, but clarity is. The hard lessons will stick, and your team becomes immune to mediocrity. After this, they’ll be more than competent: they’ll be dangerous. It Turns Failure Into Success Even if it “fails,” it doesn’t. People appreciate balls. The audacity of your move becomes its own currency, generating buzz, controversy, and respect—all of which could bag you a new client, partner, or investor. In a one-person campaign, failure is just another kind of success. How To Execute A Campaign That Borders On Maniacal Step 1: Pick Your Whale A Dream Customer: E.g., the enterprise client whose logo would give your sales team goosebumps.A Key Partner: E.g., the CMO that could double your reach if they said yes.An Influential Investor: Not just for the check, but for the name on the cap table. Be ambitious, but realistic. Elon’s too busy running Government Efficiency. Aim for the guys two rungs below him. Step 2: Stalk Your Prey Just because you’re targeting one person doesn’t mean you get to skip the user insight phase. Oh no, this research matters even more when you’re professing love, and it doesn’t stop at their LinkedIn profile. Do they like having their ego massaged? Have a fetish for cryptic puzzles? Are they nosing around for gaming collaborations? Stalk (ethically), snoop (strategically), and build a dossier so good it’d make the FBI sweat. Just remember there’s a fine line between research and “why is there a black van outside my house?” Step 3: Unleash Controlled Madness. Now that you understand your whale’s appetite, cook up the bait. Go brazen, or don’t bother. But your bravado and performance art means nothing without an unapologetic CTA and irresistible pitch. That ask needs to be so direct it’s borderline confrontational, and that pitch better feel like a bespoke Italian suit. Here are some thought-starters: Sponsor Their Daily Coffee: Find out where they get their morning coffee and prepay for a week of their orders. Include a personalized note on every receipt that says: “Fuel for your next great decision—working with us.” Ship A Literal Door: Send them a door (yes, an actual door) with a key attached and a note: “This is the key to unlocking something extraordinary. Let’s talk.” Buy An Editorial: Call up some prestigious publication they subscribe to and splurge on a paid piece. Write an open letter addressed to them, full of specifics about why they should engage with you. Be cheeky: “Hey [Their Name], Playing Small Looks Weird on You.” Step 4: Make Sure The World Knows You’re Crazy. Exclusivity is no fun if no one’s watching. Turn your serenade into a spectacle. More thought-starters: Build a Public Countdown: Launch a countdown clock on social media, with posts teasing, “6 Days Until [Target’s Name] Changes Everything.” Make sure they’re mentioned, their employees are tagged, their peers are targeted. Go Guerrilla (Literally): Hire street performers or actors to “protest” outside their HQ, carrying signs with slogans like, “[Target’s Name], Take the Meeting!”. Extra karma if it’s themed to their industry or product. Rent Their Attention: Buy ad space outside their office. A billboard. Graffiti a building (legally). Be loud to the point you start the water cooler gossip: “Dear [Name], If You Don’t Call Us, We’ll Have to Buy More Billboards. And That’s Awkward for Everyone.” Final Thoughts: Maybe It’s Not You—Maybe It’s Just Dumb Sometimes, you’re not bad at the game—the game is (likely) a waste of time. Holiday marketing for startups? That’s the house always winning, with you just the festive confetti. Stop groveling for attention in a system that turns startups into cannon fodder for ad giants. That’s not persistence—it’s herd mentality dressed up as hustle. Do something irrationally ambitious. Go unhinged, go nuclear. Not because it’s guaranteed success, but because it’s not preordained defeat. At least you’ll have had some fun, and failed in style—on your own terms, not theirs. It’s Christmas. Use the season for what it’s meant for—walking away from bad ideas. Holiday marketing, as it’s preached, is a con. A ritualized scam sold to startups by ad platforms, agencies, and marketers who profit from your desperation. Do you really think you can outspend Amazon, out-charm Coca-Cola, or outmaneuver Nike? Unless you’re secretly printing money in your garage, no. Holiday marketing, as it’s preached, is a con. Christmas isn’t for playing Santa with jingles and 20% off codes—it’s for hunting a whale. Next year, turn your entire marketing strategy into a public obsession with one person. Not a “demographic market.” Not a target persona. A single, breathing, flesh-and-blood human being whose “yes”could grant you permanent access to Cuban’s Cabo cocktail club. Next year, turn your entire marketing strategy into a public obsession with one person. Bet it all on a campaign so precise it’s borderline psychotic . Dangerous? Stupid? Obviously, and probably. But boring? Never. so precise it’s borderline psychotic so precise it’s borderline psychotic But boring? Never. If it crashes, people will talk. If it flies, you’ll own the year. Either is better than begging the Internet for clicks, plus it’ll give you a great story (or a great excuse to drink). Holiday Marketing Sucks. Holiday Marketing Sucks. This is a classic David vs. Goliath scenario— except Goliath has a machine gun and David forgot his slingshot . Here’s why it’s a losing battle: except Goliath has a machine gun and David forgot his slingshot except Goliath has a machine gun and David forgot his slingshot You’re Outgunned And Outclassed You’re Outgunned And Outclassed Every big brand with deep pockets is jacking up CPMs. Ad costs more than double, competition spikes, and algorithms prioritize whoever spends the most. Yeah, obviously not you. If your $10K campaign could talk, it would whisper: "Help." If your $10K campaign could talk, it would whisper: "Help." You’re Selling To Zombies You’re Selling To Zombies By mid-December, your CTA is competing with drunken relatives, shipping delays, and 87 ads about the perfect gift for canine therapists. Your audience is fried and their brains are coasting on autopilot—barely capable of choosing between two brands of wrapping paper. You’re Competing With Santa Claus—Not Other Businesses You’re Competing With Santa Claus—Not Other Businesses Know why Apple kills it every Christmas? It’s not with Siri, but with sentiment . The holiday giants use their war chests to craft masterpieces that ride on the emotional meaning of the season —nostalgia, tradition, family values—and if you’re not on par, you come off like a door-to-door salesman in a Saint Nick suit. sentiment that ride on the emotional meaning of the season that ride on the emotional meaning of the season ROI = Regret On Investment ROI = Regret On Investment December sales bring January sobs. Whatever you make from your festive push will be eaten alive by your CPA —and you’ll wake up next month drowning in remorse, invoices, and wondering where the cash went. (Hint: Zuck’s back pocket) Whatever you make from your festive push will be eaten alive by your CPA Whatever you make from your festive push will be eaten alive by your CPA Why Serenading One Person Is The Smartest Play Why Serenading One Person Is The Smartest Play The best presents don’t come in mass-produced packages. Neither should your holiday marketing. A custom campaign is as much a gift to them as it is to you. A custom campaign is as much a gift to them as it is to you. A custom campaign is as much a gift to them as it is to you. It’s Psychological Warfare It’s Psychological Warfare People hate being sold to, but they love feeling chosen. Focusing on one person creates a psychological bind: If they respond, they know they’re winning because you’ve done all the work to court them. If they don’t respond, they wonder if someone else will—and if they’ll miss their shot. If they respond, they know they’re winning because you’ve done all the work to court them. If they don’t respond, they wonder if someone else will—and if they’ll miss their shot. It’s The Ultimate Litmus Test For Your Product It’s The Ultimate Litmus Test For Your Product If you can’t convince one perfect-fit customer, how will you convince hundreds? A campaign por uno is the fastest way to figure out if your pitch, product, and strategy are sharp enough to scale. It’s The Best Marketing Boot Camp It’s The Best Marketing Boot Camp A one-person campaign is combat training. No crutches of generic strategies, no Canva, no “but our CTR was decent” excuses—survival here relies on raw ingenuity, superhuman agility, and uncompromising precision. Success isn’t guaranteed, but clarity is. The hard lessons will stick, and your team becomes immune to mediocrity. After this, they’ll be more than competent: they’ll be dangerous. Success isn’t guaranteed, but clarity is. It Turns Failure Into Success It Turns Failure Into Success Even if it “fails,” it doesn’t. People appreciate balls. The audacity of your move becomes its own currency, generating buzz, controversy, and respect— all of which could bag you a new client, partner, or investor. In a one-person campaign, failure is just another kind of success. all of which could bag you a new client, partner, or investor. all of which could bag you a new client, partner, or investor. How To Execute A Campaign That Borders On Maniacal How To Execute A Campaign That Borders On Maniacal Step 1: Pick Your Whale Step 1: Pick Your Whale A Dream Customer: E.g., the enterprise client whose logo would give your sales team goosebumps. A Key Partner: E.g., the CMO that could double your reach if they said yes. An Influential Investor: Not just for the check, but for the name on the cap table. A Dream Customer: E.g., the enterprise client whose logo would give your sales team goosebumps. A Dream Customer: A Key Partner: E.g., the CMO that could double your reach if they said yes. A Key Partner: An Influential Investor: Not just for the check, but for the name on the cap table. An Influential Investor: Be ambitious, but realistic. Elon’s too busy running Government Efficiency. Aim for the guys two rungs below him. Step 2: Stalk Your Prey Step 2: Stalk Your Prey Just because you’re targeting one person doesn’t mean you get to skip the user insight phase . Oh no, this research matters even more when you’re professing love, and it doesn’t stop at their LinkedIn profile. Do they like having their ego massaged? Have a fetish for cryptic puzzles? Are they nosing around for gaming collaborations? doesn’t mean you get to skip the user insight phase doesn’t mean you get to skip the user insight phase Stalk (ethically), snoop (strategically), and build a dossier so good it’d make the FBI sweat. Just remember there’s a fine line between research and “why is there a black van outside my house?” Just remember there’s a fine line between research and “why is there a black van outside my house?” Step 3: Unleash Controlled Madness. Step 3: Unleash Controlled Madness. Now that you understand your whale’s appetite, cook up the bait. Go brazen, or don’t bother. But your bravado and performance art means nothing without an unapologetic CTA and irresistible pitch. That ask needs to be so direct it’s borderline confrontational , and that pitch better feel like a bespoke Italian suit. But your bravado and performance art means nothing without an unapologetic CTA and irresistible pitch. so direct it’s borderline confrontational Here are some thought-starters: Here are some thought-starters: Sponsor Their Daily Coffee: Find out where they get their morning coffee and prepay for a week of their orders. Include a personalized note on every receipt that says: “ Fuel for your next great decision—working with us. ” Sponsor Their Daily Coffee: Fuel for your next great decision—working with us. Ship A Literal Door: Send them a door (yes, an actual door) with a key attached and a note: “ This is the key to unlocking something extraordinary. Let’s talk. ” Ship A Literal Door: This is the key to unlocking something extraordinary. Let’s talk. Buy An Editorial: Call up some prestigious publication they subscribe to and splurge on a paid piece. Write an open letter addressed to them, full of specifics about why they should engage with you. Be cheeky: “ Hey [Their Name], Playing Small Looks Weird on You .” Buy An Editorial: Hey [Their Name], Playing Small Looks Weird on You Step 4: Make Sure The World Knows You’re Crazy. Step 4: Make Sure The World Knows You’re Crazy. Exclusivity is no fun if no one’s watching. Turn your serenade into a spectacle. More thought-starters: More thought-starters: Build a Public Countdown: Launch a countdown clock on social media, with posts teasing, “ 6 Days Until [Target’s Name] Changes Everything. ” Make sure they’re mentioned, their employees are tagged, their peers are targeted. Build a Public Countdown: 6 Days Until [Target’s Name] Changes Everything. Go Guerrilla (Literally) : Hire street performers or actors to “protest” outside their HQ, carrying signs with slogans like, “ [Target’s Name], Take the Meeting! ”. Extra karma if it’s themed to their industry or product. Go Guerrilla (Literally) [Target’s Name], Take the Meeting! Rent Their Attention: Buy ad space outside their office. A billboard. Graffiti a building (legally). Be loud to the point you start the water cooler gossip: “ Dear [Name], If You Don’t Call Us, We’ll Have to Buy More Billboards. And That’s Awkward for Everyone. ” Rent Their Attention: Dear [Name], If You Don’t Call Us, We’ll Have to Buy More Billboards. And That’s Awkward for Everyone. Final Thoughts: Maybe It’s Not You—Maybe It’s Just Dumb Final Thoughts: Maybe It’s Not You—Maybe It’s Just Dumb Sometimes, you’re not bad at the game—the game is (likely) a waste of time. Holiday marketing for startups? That’s the house always winning, with you just the festive confetti. Stop groveling for attention in a system that turns startups into cannon fodder for ad giants. That’s not persistence— it’s herd mentality dressed up as hustle . Do something irrationally ambitious. Go unhinged, go nuclear . Not because it’s guaranteed success, but because it’s not preordained defeat. At least you’ll have had some fun, and failed in style— on your own terms, not theirs . it’s herd mentality dressed up as hustle it’s herd mentality dressed up as hustle Go unhinged, go nuclear Not because it’s guaranteed success, but because it’s not preordained defeat. on your own terms, not theirs It’s Christmas. Use the season for what it’s meant for—walking away from bad ideas. It’s Christmas. Use the season for what it’s meant for—walking away from bad ideas.

Next Holiday Season, Ignore Everyone Except One Customer

I næste feriesæson, ignorer alle undtagen én kunde

La próxima temporada navideña, ignore a todos excepto a un cliente

Sljedeće blagdanske sezone zanemarite sve osim jednog kupca

次のホリデーシーズンは、1人の顧客以外全員を無視する

შემდეგი სადღესასწაულო სეზონი, იგნორირება გაუკეთეთ ყველას გარდა ერთი მომხმარებლისა

រដូវកាលឈប់សម្រាកបន្ទាប់ មិនអើពើនឹងអ្នកគ្រប់គ្នា លើកលែងតែអតិថិជនម្នាក់

다음 휴가 시즌에는 한 명의 고객을 제외한 모든 사람을 무시하세요

Saison ya ba fêtes oyo ekoya, Ignorer mutu nionso sauf Client moko

Hamuq Fiesta pacha, Llapa runata mana kasuychu, huk rantiqmanta aswanta

Следеће празничне сезоне, игноришите све осим једног купца

Susunod na Holiday Season, Balewalain ang Lahat Maliban sa Isang Customer

Keyingi bayram mavsumida bitta mijozdan tashqari hammaga e'tibor bermang

Codebase Migration: How to Successfully Migrate a Codebase

Skyecap is a fintech company founded in 2018 by Andrew Spira, with a mission to change how small and medium enterprises (SMEs) in Australia access capital. Dissatisfied with the slow and rigid processes of traditional banks, Spira imaged a faster, more flexible, and accessible lending solution. Over its years of operation, Skyecap has grown into a major figure within the private lending sector, providing thousands of businesses with the funding they need to thrive. The Birth of Skyecap: A Vision for Accessible Business Funding Born out of Spira’s firsthand experience with the challenges SMEs face when dealing with traditional banks, Skyecap was originally founded to provide opportunities to the underserved or overlooked. These challenges included lengthy loan approval processes, rigid lending criteria, and excessive paperwork. In order to address these issues, Spira integrated advanced technology into Skyecap’s operations from day one. The company developed SkyeAI, a proprietary artificial intelligence algorithm that encapsulates the entire loan application process. The platform allows Skyecap to assess applications in real-time, allowing interested businesses to apply online within minutes and receive funds within two hours of approval. Skyecap’s Rapid Growth Even from its initial launch, Skyecap has achieved remarkable growth. By 2024, the company had onboarded over 75,000 clients and increased its customer base by an impressive 489% in that year alone. Such success aligns with a noted increase in the demand for more flexible and accessible funding options for SMEs. Notably, more than 60% of Skyecap's clients had previously been rejected by traditional lenders. Using AI-driven analytics that follows alternative routes conventional credit scores and financial statements tend to miss, Skyecap identifies potential in businesses otherwise denied by traditional banks. It is this system that has allowed the company to tap into a "hidden economy" of underserved businesses. Skyecap’s SkyeAI algorithm is, according to Spira himself, the main cause of the company’s success. Unlike traditional lenders that rely on outdated metrics, SkyeAI analyzes diverse data points such as social media sentiment, local economic trends, and cash flow patterns. Such comprehensive analysis gives way for faster approvals while maintaining a low default rate of just 2.5%, significantly below industry averages. How Skyecap Stands Out from Traditional Banks Holistically, Skyecap differentiates itself from traditional banks through three key pillars: speed, flexibility, and accessibility. Speed Perhaps Skyecap's most significant advantage is its lightning-fast approval process. Traditional banks often take weeks or months to process loan applications due to manual reviews and outdated systems. In comparison, Skyecap uses AI-powered technology to make real-time decisions. Once approved, funds are transferred within two hours–an unheard-of capacity for SMEs needing immediate capital for urgent needs like equipment purchases or cash flow management. 2. Flexibility Skyecap has also established its reputation for flexibility. Unlike traditional banks that typically require significant assets as collateral, Skyecap offers unsecured loans ranging from $2,000 to $250,000 AUD without requiring collateral at all. Borrowers also enjoy the freedom to use funds as needed–whether for workforce expansion, technology upgrades, or marketing campaigns–rather than being restricted to specific purposes imposed by the lender. 3. Accessibility Finally, Skyecap excels in accessibility by opening its doors to businesses that seek to break the mold within their industry. While banks tend to favor larger businesses with established financial histories, proven concepts, and high credit scores, Skyecap’s AI-driven methods look beyond these conventional metrics. Analyzing broader data sets such as market trends and cash flow patterns, SkyeAI identifies promising businesses with strong growth potential even if they do not meet traditional criteria. Such a strategy has proven to be particularly valuable during economic downturns when many SMEs face cash flow challenges that would typically disqualify them under traditional banking standards. A New Era of Business Lending Skyecap is among the first of its kind within the SME lending industry, where it is best known for addressing the inefficiencies of traditional banking systems through technology. With fast approvals, flexible terms, and data-driven decisions based on business potential, Skyecap helps Australian SMEs thrive in an otherwise hostile economy. More than another investment and funding company, Skyecap seeks to represent an ideal–one where an idea, no matter how out-of-the-box, can be explored. From highly advanced technology labs to small enterprises built on life-long dreams, Andrew Spira and Skyecap seek opportunities for all. Photo credit: Skyecap Skyecap is a fintech company founded in 2018 by Andrew Spira , with a mission to change how small and medium enterprises (SMEs) in Australia access capital. Dissatisfied with the slow and rigid processes of traditional banks, Spira imaged a faster, more flexible, and accessible lending solution. Over its years of operation, Skyecap has grown into a major figure within the private lending sector, providing thousands of businesses with the funding they need to thrive. Skyecap Skyecap Andrew Spira Andrew Spira The Birth of Skyecap: A Vision for Accessible Business Funding The Birth of Skyecap: A Vision for Accessible Business Funding Born out of Spira’s firsthand experience with the challenges SMEs face when dealing with traditional banks, Skyecap was originally founded to provide opportunities to the underserved or overlooked. These challenges included lengthy loan approval processes, rigid lending criteria, and excessive paperwork. In order to address these issues, Spira integrated advanced technology into Skyecap’s operations from day one. The company developed SkyeAI, a proprietary artificial intelligence algorithm that encapsulates the entire loan application process. The platform allows Skyecap to assess applications in real-time, allowing interested businesses to apply online within minutes and receive funds within two hours of approval. Skyecap’s Rapid Growth Skyecap’s Rapid Growth Even from its initial launch, Skyecap has achieved remarkable growth. By 2024, the company had onboarded over 75,000 clients and increased its customer base by an impressive 489% in that year alone. Such success aligns with a noted increase in the demand for more flexible and accessible funding options for SMEs. Notably, more than 60% of Skyecap's clients had previously been rejected by traditional lenders. Using AI-driven analytics that follows alternative routes conventional credit scores and financial statements tend to miss, Skyecap identifies potential in businesses otherwise denied by traditional banks. It is this system that has allowed the company to tap into a "hidden economy" of underserved businesses. Skyecap’s SkyeAI algorithm is, according to Spira himself, the main cause of the company’s success. Unlike traditional lenders that rely on outdated metrics, SkyeAI analyzes diverse data points such as social media sentiment, local economic trends, and cash flow patterns. Such comprehensive analysis gives way for faster approvals while maintaining a low default rate of just 2.5%, significantly below industry averages. How Skyecap Stands Out from Traditional Banks How Skyecap Stands Out from Traditional Banks Holistically, Skyecap differentiates itself from traditional banks through three key pillars: speed, flexibility, and accessibility. Speed Speed Speed Perhaps Skyecap's most significant advantage is its lightning-fast approval process. Traditional banks often take weeks or months to process loan applications due to manual reviews and outdated systems. In comparison, Skyecap uses AI-powered technology to make real-time decisions. Once approved, funds are transferred within two hours–an unheard-of capacity for SMEs needing immediate capital for urgent needs like equipment purchases or cash flow management. 2. Flexibility Skyecap has also established its reputation for flexibility. Unlike traditional banks that typically require significant assets as collateral, Skyecap offers unsecured loans ranging from $2,000 to $250,000 AUD without requiring collateral at all. Borrowers also enjoy the freedom to use funds as needed–whether for workforce expansion, technology upgrades, or marketing campaigns–rather than being restricted to specific purposes imposed by the lender. 3. Accessibility Finally, Skyecap excels in accessibility by opening its doors to businesses that seek to break the mold within their industry. While banks tend to favor larger businesses with established financial histories, proven concepts, and high credit scores, Skyecap’s AI-driven methods look beyond these conventional metrics. Analyzing broader data sets such as market trends and cash flow patterns, SkyeAI identifies promising businesses with strong growth potential even if they do not meet traditional criteria. Such a strategy has proven to be particularly valuable during economic downturns when many SMEs face cash flow challenges that would typically disqualify them under traditional banking standards. A New Era of Business Lending A New Era of Business Lending Skyecap is among the first of its kind within the SME lending industry, where it is best known for addressing the inefficiencies of traditional banking systems through technology. With fast approvals, flexible terms, and data-driven decisions based on business potential, Skyecap helps Australian SMEs thrive in an otherwise hostile economy. More than another investment and funding company, Skyecap seeks to represent an ideal–one where an idea, no matter how out-of-the-box, can be explored. From highly advanced technology labs to small enterprises built on life-long dreams, Andrew Spira and Skyecap seek opportunities for all. Photo credit: Skyecap Photo credit: Skyecap Photo credit: Skyecap

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