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A SHORT CHRONICLE

The Chronology of Ancient Kingdoms Amendedby Isaac Newton, is part of the HackerNoon Books Series. You can jump to any chapter in this book here . The INTRODUCTION The INTRODUCTION. The Greek Antiquities are full of Poetical Fictions, because the Greeks wrote nothing in Prose, before the Conquest of Asia by Cyrus the Persian. Then Pherecydes Scyrius and Cadmus Milesius introduced the writing in Prose. Pherecydes Atheniensis, about the end of the Reign of Darius Hystaspis, wrote of Antiquities, and digested his work by Genealogies, and was reckoned one of the best Genealogers. Epimenides the Historian proceeded also by Genealogies; and Hellanicus, who was twelve years older than Herodotus, digested his History by the Ages or Successions of the Priestesses of Juno Argiva. Others digested theirs by the Kings of the Lacedæmonians, or Archons of Athens. Hippias the Elean, about thirty years before the fall of the Persian Empire, published a breviary or list of the Olympic Victors; and about ten years before the fall thereof, Ephorus the disciple of Isocrates formed a Chronological History of Greece, beginning with the return of the Heraclides into Peloponnesus, and ending with the siege of Perinthus, in the twentieth year of Philip the father of Alexander the great: But he digested things by Generations, and the reckoning by Olympiads was not yet in use, nor doth it appear that the Reigns of Kings were yet set down by numbers of years. The Arundelian marbles were composed sixty years after the death of Alexander the great (An. 4. Olymp. 128.) and yet mention not the Olympiads: But in the next Olympiad, Timæus Siculus published an history in several books down to his own times, according to the Olympiads, comparing the Ephori, the Kings of Sparta, the Archons of Athens, and the Priestesses of Argos, with the Olympic Victors, so as to make the Olympiads, and the Genealogies and Successions of Kings, Archons, and Priestesses, and poetical histories suit with one another, according to the best of his judgment. And where he left off, Polybius began and carried on the history. So then a little after the death of Alexander the great, they began to set down the Generations, Reigns and Successions, in numbers of years, and by putting Reigns and Successions equipollent to Generations, and three Generations to an hundred or an hundred and twenty years (as appears by their Chronology) they have made the Antiquities of Greece three or four hundred years older than the truth. And this was the original of the Technical Chronology of the Greeks. Eratosthenes wrote about an hundred years after the death of Alexander the great: He was followed by Apollodorus, and these two have been followed ever since by Chronologers. But how uncertain their Chronology is, and how doubtful it was reputed by the Greeks of those times, may be understood by these passages of Plutarch. Some reckon, saith he, Lycurgus contemporary to Iphitus, and to have been his companion in ordering the Olympic festivals: amongst whom was Aristotle the Philosopher, arguing from the Olympic Disc, which had the name of Lycurgus upon it. Others supputing the times by the succession of the Kings of the Lacedæmonians, as Eratosthenes and Apollodorus, affirm that he was not a few years older than the first Olympiad. First Aristotle and some others made him as old as the first Olympiad; then Eratosthenes, Apollodorus, and some others made him above an hundred years older: and in another place Plutarch tells us: The congress of Solon with Croesus, some think they can confute by Chronology. But an history so illustrious, and verified by so many witnesses, and (which is more) so agreeable to the manners of Solon, and so worthy of the greatness of his mind and of his wisdom, I cannot persuade my self to reject because of some Chronological Canons, as they call them: which hundreds of authors correcting, have not yet been able to constitute any thing certain, in which they could agree among themselves, about repugnancies. It seems the Chronologers had made the Legislature of Solon too ancient to consist with that Congress. For reconciling such repugnancies, Chronologers have sometimes doubled the persons of men. So when the Poets had changed Io the daughter of Inachus into the Egyptian Isis, Chronologers made her husband Osiris or Bacchus and his mistress Ariadne as old as Io, and so feigned that there were two Ariadnes, one the mistress of Bacchus, and the other the mistress of Theseus, and two Minos's their fathers, and a younger Io the daughter of Jasus, writing Jasus corruptly for Inachus. And so they have made two Pandions, and two Erechtheus's, giving the name of Erechthonius to the first; Homer calls the first, Erechtheus: and by such corruptions they have exceedingly perplexed Ancient History. And as for the Chronology of the Latines, that is still more uncertain. Plutarch represents great uncertainties in the Originals of Rome: and so doth Servius. The old records of the Latines were burnt by the Gauls, sixty and four years before the death of Alexander the great; and Quintus Fabius Pictor, the oldest historian of the Latines, lived an hundred years later than that King. In Sacred History, the Assyrian Empire began with Pul and Tiglathpilaser, and lasted about 170 years. And accordingly Herodotus hath made Semiramis only five generations, or about 166 years older than Nitocris, the mother of the last King of Babylon. But Ctesias hath made Semiramis 1500 years older than Nitocris, and feigned a long series of Kings of Assyria, whose names are not Assyrian, nor have any affinity with the Assyrian names in Scripture. The Priests of Egypt told Herodotus, that Menes built Memphis and the sumptuous temple of Vulcan, in that City: and that Rhampsinitus, Mœris, Asychis and Psammiticus added magnificent porticos to that temple. And it is not likely that Memphis could be famous, before Homer's days who doth not mention it, or that a temple could be above two or three hundred years in building. The Reign of Psammiticus began about 655 years before Christ, and I place the founding of this temple by Menes about 257 years earlier: but the Priests of Egypt had so magnified their Antiquities before the days of Herodotus, as to tell him that from Menes to Mœris (who reigned 200 years before Psammiticus) there were 330 Kings, whose Reigns took up as many Ages, that is eleven thousand years, and had filled up the interval with feigned Kings, who had done nothing. And before the days of Diodorus Siculus they had raised their Antiquities so much higher, as to place six, eight, or ten new Reigns of Kings between those Kings, whom they had represented to Herodotus to succeed one another immediately. In the Kingdom of Sicyon, Chronologers have split Apis Epaphus or Epopeus into two Kings, whom they call Apis and Epopeus, and between them have inserted eleven or twelve feigned names of Kings who did nothing, and thereby they have made its Founder Ægialeus, three hundred years older than his brother Phoroneus. Some have made the Kings of Germany as old as the Flood: and yet before the use of letters, the names and actions of men could scarce be remembred above eighty or an hundred years after their deaths: and therefore I admit no Chronology of things done in Europe, above eighty years before Cadmus brought letters into Europe; none, of things done in Germany, before the rise of the Roman Empire. Now since Eratosthenes and Apollodorus computed the times by the Reigns of the Kings of Sparta, and (as appears by their Chronology still followed) have made the seventeen Reigns of these Kings in both Races, between the Return of the Heraclides into Peloponnesus and the Battel of Thermopylæ, take up 622 years, which is after the rate of 36½ years to a Reign, and yet a Race of seventeen Kings of that length is no where to be met with in all true History, and Kings at a moderate reckoning Reign but 18 or 20 years a-piece one with another: I have stated the time of the return of the Heraclides by the last way of reckoning, placing it about 340 years before the Battel of Thermopylæ. And making the Taking of Troy eighty years older than that Return, according to Thucydides, and the Argonautic Expedition a Generation older than the Trojan War, and the Wars of Sesostris in Thrace and death of Ino the daughter of Cadmus a Generation older than that Expedition: I have drawn up the following Chronological Table, so as to make Chronology suit with the Course of Nature, with Astronomy, with Sacred History, with Herodotus the Father of History, and with it self; without the many repugnancies complained of by Plutarch. I do not pretend to be exact to a year: there may be Errors of five or ten years, and sometimes twenty, and not much above. About HackerNoon Book Series: We bring you the most important technical, scientific, and insightful public domain books. This book is part of the public domain. Isaac Newton (2005). Chronology of Ancient Kingdoms Amended. Urbana, Illinois: Project Gutenberg. Retrieved October 2022, https://www.gutenberg.org/cache/epub/15784/pg15784-images.html This eBook is for the use of anyone anywhere at no cost and with almost no restrictions whatsoever. You may copy it, give it away or re-use it under the terms of the Project Gutenberg License included with this eBook or online at www.gutenberg.org , located at https://www.gutenberg.org/policy/license.html.

The INTRODUCTION

The Essays of Adam Smith: Part VII, Section II, Chapter I

Lead image via PopSugar Impulsive purchases are usually made at the shelf-edge, usually while browsing which makes up about 76 percent of consumers. The use of shelf-edge placement is a classic marketing tool usually used in retail. Paper printed labels have been the staple in most retail stores, providing information on the price of goods. However, a , a portion of this from the retail industry causing the ever-growing problems of deforestation. bout 1 billion trees worth of paper are generally thrown out each year Digital technology has entered this contemporary society, readily integrating itself in the majority of the industry especially the fashion and retail industry to connect the best of both the online and offline shopping scene. Shelf-edge technology is one of the few up-and-coming technologies that could change the whole experience of shopping. Digital Transition As of now, the most to gain from shelf-edge technology is mainly grocers and retail as large stores spend a huge budget and time in changing the paper tags manually, between 5 to 10 million labels a week for huge retail stores. Taking the next step with digital transition could easily solve this problem. Retailers understand the pros entailed in undergoing a digital transition as it increases . Aside from this, about 55% of retailers focus on general industry price change which is important in the industry. price sensitivity amongst customers (57%) and promotional intensity among competitors (41%) Image via Elle What are Digital Tags? Digital tags from edge technology are basically electronic shelf labels that are able to showcase the price per row. Allowing more opportunities for retailers to become more sensitive to pricing strategies. Enabling brands to create different campaigns and strategies that could help with both internal and external problems. Enabling brands to change pricing of seasonal collections such as Zara to certain offers and markdowns. The ability of brands to quickly update prices into a more centralized and enterprise-like approach could easily reduce labor and operational costs. Benefits Fixed price guarantee for consumers Endless price changes protecting margins Fast reaction to price change against competitors Lower staff labor Lower operational costs Versatile promotional ePaper campaigns Employees focus more on consumers shopping experience Reduce paper waste Shelf-Life Future The growing industry of retail is not only restricted to the idea of a digital price tag as an alternative to increase operational advantage and build customer loyalty. The battery life is another factor that must be accounted in the study of digital price tags as it does not only accommodate floor automation use, but also improvement of electronic shelf labels. Digital price tags can easily help retailers and businesses provide a more centralized experience and focused experience. Allowing fashion brands to showcase a different approach of pricing that could be graphically pleasing and high-performance based. Image via UBCSustainability Sustainable Implications Edge digital shelf display technology is not only a highly performative pricing and operational strategy it is sustainable. Its provide a more interactive shopping experience according to partner Microsoft. Using renewable energy and lessening the current use of printed tags. As Microsoft has stated: Edge is designed to use a low voltage, direct current that meets the standards of emerge alliance, an organization that promotes sustainable power usage in commercial buildings. Edge sustainability goals which is cutting down 40% of electricity consumption of its entire system is pushed through the companies principles and forward-thinking strategies sustainable benefits Gif via Dazed Current Use Currently, about 16 stores are using ESL (electronic shelf labels) or Digital Tags through Edge which will steadily expand to 120 by 2022 as Microsoft has exclaimed. Although digital labels aren’t literally new, it has not been clearly adopted commercially as a whole. However, we encourage businesses and retailers to consider the possibility of its benefits, as a typical store requires about 20,000 price displays and tags.

Shelf Edge Technology: Digital Price Tags Using Renewable Energy

About a year ago I wrote about with a Raspberry Pi and a cheap sensor. Make sure to read that article first! We’ve been using this setup in our school and privately for a few years now. However, this project has one disadvantage: it is not portable, but depends on a WLAN network or a wired network connection. You actually cannot access the measurements if the Raspberry Pi and the smartphone or computer are not in the same network. That’s why some time ago we added a small screen to the Raspberry Pi so that you can read the values directly from the device. How to set up this screen for our mobile fine particulate matter sensor and which additional configurations are necessary, I would like to describe in this article. how to measure the air quality Setting up the screen for the Raspberry Pi On or AliExpress there are different displays for the Raspberry Pi. These range from ePaper screens to LCDs with touch function. We chose a with touch, that has a resolution of 320×480 pixels (model MPI3501). You can simply plug this screen onto the GPIO pins. It costs only 10–20$. It’s also nice that a 3,5″ display is about the same size like a Raspberry Pi. Amazon 3,5″ LCD If you put on the screen and start the Raspberry Pi, the screen stays white. That normal, because the driver is missing. You have to install the appropriate drivers for the display first. To do this, log in via SSH and execute the following commands: $ rm -rf LCD-show$ git clone $ chmod -R 755 LCD-show$ cd LCD-show/ https://github.com/goodtft/LCD-show.git Depending on the screen model you have to execute the appropriate command to install the drivers. In our case (for the model MPI3501): $ sudo ./LCD35-show This command installs the appropriate drivers and then restarts the Raspberry Pi. Installing the Pixel Desktop and Setting Up Autostart Here is what we want: if the Raspberry Pi boots up we want to display our small website with the measurements. So first you have to install the pixel desktop environment (if you have used Raspian Lite before) with $ sudo apt install raspberrypi-ui-mods Then the Chromium browser (we need it to display the website): $ sudo apt install chromium-browser By default, the autologin is not configured for the user “pi”. However, this is necessary so that the measured values can be displayed directly after the start. Otherwise you will only see the login screen. You can configure the autologin with the tool: raspi-config In the menu select . 3 Boot Options → B1 Desktop / CLI → B4 Desktop Autologin There is one step missing to start chromium right after bootup with our website. Create the folder : /home/pi/.config/lxsession/LXDE-pi/ $ mkdir -p /home/pi/config/lxsession/LXDE-pi/ Then create the file in this folder. autostart $ nano /home/pi/.config/lxsession/LXDE-pi/autostart and paste the following code: #@unclutter@xset s off@xset -dpms@xset s noblank # Open Chrome in full screen mode after boot@chromium-browser — incognito — kiosk http://localhost If you want to hide the mouse pointer, you have to install the package and remove the comment character at the beginning of the file: unclutter autostart $ sudo apt install unclutter Since I made a few small changes to the code last year, it is recommended to re-download the script and the files of the AQI website (see the for how to do this). original article Conclusion With the touch screen added you now have a mobile particulate matter sensor! We use it at our school to check the quality of the air in the classrooms or to do comparative measurements. With this setup, you are no longer dependent on a network connection or WLAN. You can use the small measuring station everywhere — with a power bank even independent of the power grid. Originally published at openschoolsolutions.org .

How to Build a Mobile Particulate Matter Sensor

Introduction: Data engineering has evolved into specialized fields like DataOps and VectorOps to address the challenges of managing data and vector embeddings, respectively. As large language models (LLMs) like GPT-4 emerge, managing high-dimensional data structures becomes increasingly important. LangChain, an LLM-powered application development framework, integrates with DataOps and VectorOps processes and utilizes vector databases to create data-aware, interactive applications. DataOps: Streamlining Data Management and Processes: DataOps focuses on enhancing collaboration, integration, and automation of data flows across organizations. Implementing DataOps practices promotes data accuracy, consistency, and accessibility, which are vital for data-aware applications using LLMs. Key DataOps technologies include Apache Kafka for real-time data streaming, Apache Airflow for workflow management, and Apache NiFi for data routing and transformation. References: https://medium.com/codex/5-steps-to-implementing-a-successful-dataops-practice-f553effd7367 https://www.forbes.com/sites/forbesbusinessdevelopmentcouncil/2022/01/24/how-to-implement-a-successful-dataops-strategy-and-why-it-matters/?sh=56e354d5e87c https://www.linkedin.com/pulse/dataops-practical-understanding-implementation-taaha-khan-/ VectorOps: Tackling High-Dimensional Data Challenges: VectorOps specializes in managing vector embeddings, a critical component of LLMs. Traditional databases struggle with high-dimensional data structures, whereas vector databases excel in handling them. Integrating VectorOps with DataOps processes enables efficient large-scale vector embedding management, paving the way for innovative applications using LLMs. Popular vector database technologies used in VectorOps include FAISS, Milvus, and Pinecone. References: https://thenewstack.io/vector-databases-long-term-memory-for-artificial-intelligence https://www.pinecone.io/learn/vector-database/ https://techgenix.com/rise-of-vector-databases/ LangChain: Building Data-Aware LLM Applications: LangChain facilitates the development of applications that connect to data sources, interact with their environment, and utilize the power of LLMs. It offers various modules, such as Models, Prompts, Memory, Indexes, Chains, and Agents. The Indexes module focuses on structuring documents for optimal LLM interaction and retrieval, making it an excellent candidate for VectorOps and vector database integration. LangChain supports integration with LLMs like GPT-4, BERT, and RoBERTa. """
Example of creating a chat bot with GPT-Index & LangChain.
"""

from llama_index import SimpleDirectoryReader, GPTListIndex, readers, GPTSimpleVectorIndex, LLMPredictor, PromptHelper
from langchain import OpenAI
import sys
import os
from IPython.display import Markdown, display


def construct_index(directory_path):
    # set maximum input size
    max_input_size = 4096
    # set number of output tokens
    num_outputs = 2000
    # set maximum chunk overlap
    max_chunk_overlap = 20
    # set chunk size limit
    chunk_size_limit = 600 

    # define LLM
    llm_predictor = LLMPredictor(llm=OpenAI(temperature=0.5, model_name="text-davinci-003", max_tokens=num_outputs))
    prompt_helper = PromptHelper(max_input_size, num_outputs, max_chunk_overlap, chunk_size_limit=chunk_size_limit)
 
    documents = SimpleDirectoryReader(directory_path).load_data()
    
    index = GPTSimpleVectorIndex(
        documents, llm_predictor=llm_predictor, prompt_helper=prompt_helper
    )

    index.save_to_disk('index.json')

    return index

def ask_ai():
    index = GPTSimpleVectorIndex.load_from_disk('index.json')
    while True: 
        query = input("What do you want to ask? ")
        response = index.query(query, response_mode="compact")
        display(Markdown(f"Response: <b>{response.response}</b>")) References: https://python.langchain.com/en/latest/index.html https://github.com/hwchase17/langchain https://github.com/gkamradt/langchain-tutorials/blob/main/LangChain Cookbook Part 2 - Use Cases.ipynb Integrating DataOps, VectorOps, and LangChain: DataOps, VectorOps, and LangChain integration create powerful applications that combine efficient data management, high-dimensional data processing, and LLM capabilities. Some key advantages of this integration include: Enhanced similarity search: LangChain's integration with vector databases and VectorOps enables efficient near-neighbor matching, providing comprehensive results beyond traditional keyword-based searches. Scalability: DataOps and VectorOps processes ensure the efficient handling of large-scale vector embeddings, making the framework ideal for managing data in the era of LLMs and other complex models. """
As described here: https://python.langchain.com/en/latest/modules/indexes/vectorstores/examples/pinecone.html
"""

import pinecone
from langchain.embeddings.openai import OpenAIEmbeddings
from langchain.text_splitter import CharacterTextSplitter
from langchain.vectorstores import Pinecone
from langchain.document_loaders import TextLoader

loader = TextLoader('../../../state_of_the_union.txt')
documents = loader.load()
text_splitter = CharacterTextSplitter(chunk_size=1000, chunk_overlap=0)
docs = text_splitter.split_documents(documents)

embeddings = OpenAIEmbeddings()

# initialize pinecone
pinecone.init(
    api_key=PINECONE_API_KEY,  # find at app.pinecone.io
    environment=PINECONE_ENV  # next to api key in console
)

index_name = "langchain-demo"

docsearch = Pinecone.from_documents(docs, embeddings, index_name=index_name)

# if you already have an index, you can load it like this
# docsearch = Pinecone.from_existing_index(index_name, embeddings)

query = "What did the president say about Ketanji Brown Jackson"
docs = docsearch.similarity_search(query)

print(docs[0].page_content) Flexibility: LangChain allows users to perform searches based on high-level descriptions rather than relying on specific keywords or metadata classifications, enabling more versatile applications. Reference: https://mattboegner.com/knowledge-retrieval-architecture-for-llms/ https://simonwillison.net/2023/Jan/13/semantic-search-answers/ https://www.codingthesmartway.com/unlocking-the-power-of-llms-with-langchain-a-beginners-guide/ https://python.langchain.com/en/latest/modules/models/llms/integrations.html Conclusion: By focusing on DataOps, VectorOps, and LangChain, developers can create advanced, data-driven applications that leverage the power of LLMs and vector embeddings. Efficient data management through DataOps, coupled with VectorOps' expertise in high-dimensional data processing, unlocks the full potential of LLMs like GPT-4, BERT, and RoBERTa. LangChain serves as the bridge between these two fields, enabling developers to build innovative applications that can revolutionize industries and reshape the future of data-driven solutions. https://www.youtube.com/watch?v=UO699Szp82M&embedable=true As the need for data-aware applications and large-scale vector embedding management grows, the synergistic integration of DataOps, VectorOps, and LangChain will play a critical role in shaping the next generation of data-driven applications. By keeping up-to-date with the latest developments in these fields and embracing cutting-edge technologies, developers can stay ahead of the curve and lead the way toward a data-centric future.

The New Data Engineering Landscape: DataOps, VectorOps, and LangChain

TL;DR; The global gaming industry, particularly casual, hyper-casual, and mobile gaming, is growing rapidly, largely driven by advancements in advertising technology (AdTech). AdTech provides tools to manage, target, and optimize advertising campaigns, improving key gaming industry KPIs like the acquisition funnel, churn rate, retention rate, engagement, conversion rate, and game monetization. KPIs help developers pinpoint and address issues in their games, with AdTech platforms offering tools for detailed analysis and targeted advertising based on player behavior. Game monetization, another crucial KPI, relies heavily on in-app purchases, subscriptions, and ads, and AdTech plays a significant role in optimizing these for maximum revenue. Average Revenue Per User (ARPU), Average Revenue Per Paying User (ARPPU), and Lifetime Value (LTV) are key metrics in the gaming industry, and AdTech helps boost these by delivering personalized ads and enhancing player engagement. With the gaming industry projected to grow exponentially, the role of AdTech in optimizing game performance and maximizing revenue generation will become increasingly important. Introduction: AdTech's Impact on the Gaming Industry The global gaming industry, specifically casual, hyper-casual, and mobile gaming, has been on a growth trajectory. Total revenue is expected to show an annual growth rate (CAGR 2022-2027) of 8.91%, resulting in a projected market volume of US$24.97bn by 2027 ( ). This surge is largely attributed to the advancement of advertising technology, or AdTech. AdTech, with its robust tools for managing, targeting, and optimizing advertising campaigns, significantly enhances gaming industry KPIs, optimizes acquisition funnels, and maximizes game monetization. Statista, 2023 Unpacking Key KPIs in the Gaming Industry Understanding the key KPIs in the gaming industry is vital for game development success. These KPIs include acquisition funnel, churn rate, retention rate, 7 & 30-day retention, player engagement, conversion rate, and game monetization metrics. The acquisition funnel, a vital concept in gaming, represents the player's journey from game discovery to active participation. AdTech, with its precise targeting and personalized ad content capabilities, supercharges this funnel, leading to a notable 47% increase (in December 2022 for iOS) in high-value user acquisition ( ). Venturebeat, 2023 Churn and retention rates are essential KPIs too. In 2021, mobile gaming apps experienced a day-one retention rate of approximately 35-40%, According to GameAnalytics, a mobile game is considered successful if its day-1 retention is above 35% ( ). These metrics, when analyzed meticulously, help game developers pinpoint and address problem areas in their games to improve player engagement. AdTech platforms offer tools for such analysis and can also elevate retention rates through targeted advertising based on player behavior and preferences, which subsequently boosts conversion rates. Udonis, 2023 Game monetization, another critical KPI, often depends on in-app purchases, subscriptions, and ads. In 2022, mobile in-app purchase revenue globally stood at a remarkable $431 billion ( ). AdTech plays a crucial role in monetizing games by optimizing ad placements, personalizing ad content, and targeting the right users, thereby enhancing overall revenue. Statista, 2023 Calculating and Boosting ARPU, ARPPU, and LTV with AdTech Average Revenue Per User (ARPU), Average Revenue Per Paying User (ARPPU), and Lifetime Value (LTV) are indispensable metrics in the gaming industry. In 2020, the global mobile gaming ARPU was estimated at $53.71 ( ). These metrics provide essential insights into the revenue generated per user or paying user and the projected revenue over their gaming lifespan. Gitnux, 2023 AdTech has the potential to elevate these metrics significantly. By delivering personalized ads, AdTech can incentivize players to make more in-app purchases, thereby boosting ARPU and ARPPU. Furthermore, AdTech can enhance a player's LTV by offering a more engaging gaming experience through relevant ads, leading to prolonged engagement and continued revenue. Conclusion: AdTech's Growing Role in the Gaming Industry In conclusion, AdTech's impact on the gaming industry is profound. It plays an instrumental role in enhancing KPIs, optimizing the acquisition funnel, and bolstering game monetization strategies. With the total revenue in the Casual Games market projected to reach US$15.51bn in 2022 ( ), AdTech's role in fine-tuning game performance and maximizing revenue generation will undoubtedly become increasingly vital. Statista, 2023 Also appears . here

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