• Indian, Male, Non-US citizen, No Greencard
• EFC: 50-60k per year. Need aid at T20s, full pay at publics
• Private, not well known school, non-feeder. Noone goes abroad
• Hooks: I wish

• SAT: 1570 - 790 M, 780 EBRW
• Duolingo Test: 155/160
• APs: No APs in school. Took 5 on my own. Taking 4 more for 2023AP Calc BC: 5, AP Statistics: 5, AP Comp Sci A: 4, AP Phy C Mechanics: 5, AP Calc AB subscore: 5
• Taking 4 more: AP Phy C Electromagnetism, AP Macroecon, AP microeon, AP psychology

• CBSE: Math, Physics, English Core, Chemistry, Computer Science
• External APs: AP Microeconomics, AP Macroeconomics, AP Psychology, AP Phy C Electromagnetism

• CEMC Waterloo Euclid Math Contest: Distinction, Score 91/100, Ranked 50/17000+
• All India rank 4: ICSE Board Exam, 200k+ participants
• 2xValedictorian - Half tuition merit scholarship, Schoolwide, 2 times winner (2019, 2020)
• AP Scholar with Honor, (2022)
• Regional WinneBest Delegate: Panel Debate on Women's rights, Regional (2021)
• HSA Investment Bootcamp: One of the Top 10 finalists out of 160 teams. Invited to pitch to a panel of Investment-Banking Professionals in NYC
• Random Science competition: Zonal Gold medal (2021) [International rank 45]
• Random English competition: Zonal Bronze Medal (2021) [International Rank 99]
• Random Math competition: Zonal Bronze Medal (2021)

• Founder of a social organization aimed at post-Covid employment restoration: 55+ workshops, 100+ volunteers, 60+ found jobs, 700+ attendees. Partnered with UNICEF India
• Research Paper on Biometric Systems (Mentor from UMich, w/ LOR), Accepted for publication in an impact factor 5.1 journal
• Cooking for Cause: participated in & hosted 60+ community potlucks and bake sales. Managed food supply for NGOs. Raised INR 5,50,000+; helped 3000+ people. Manage food chain for 3 NGOs. partnered with a big NGO and UNICEF
• UNICEF Youth volunteer and reporter: Part of a division of 25 people, raised INR 200,000 across 8 weeks. Edited 30 blogs/e-articles for awareness. 600 people reached so far
• Deputy Head Boy Ex StuCo Member: managed Gsuite for 1500+ students. 20+ policy change campaigns
• Intern at Microsoft (MS Edge)
• Intern at Google (Google Ads + Voice Assistant)
• Founded a personal finance startup based on AI/ML/Visual data; Prelaunch and Pre-opening. App in testing. 10+ volunteers
• Team Leader, HSA Investment Bootcamp: Ranked T10 out of 160 teams. Invited to pitch to a panel in NYC
• Sole Developer of an algorithm: Mental-health tracker algorithm that acts as a virtual friend Collaborating with a local company. Patent pending
• Research Chapter in school: head of research club. Started 3 papers, with 5-6 co-authors for each
• Founder, CS For Socials club: 50 students across 8 schools. 30+ projects, 20+ small scale retailers helped

• Co-Head of the school's Entrepreneurship Club
• Leader of school Tech Club (50 hrs)
• Member of both school's Social Service Club
• Working out/Bodybuilding and local gym trainer. (2+ years)

Happy Friday, Barkada --

The PSE gained 14 points to 6645 ▲0.2%

▌In today's MB:

• JG Summit's FY22 crushed by falling peso
• DMCI declares chonky div
• Monde Nissin "rationalizes" Quorn value, loses P21-B
• Union Bank cashing up for another acquisition?

▌Daily meme Subscribe (it's free) Today's email

▌Main stories covered:

• [FY22] JG Summit net income crushed by falling peso... JG Summit [JGS 53.20 ▲1.3%] [link] previewed its FY22 earnings by revealing that its net income fell by 86% to just ₱0.7 billion, despite “record high” revenues and a doubling of its core net income to ₱6.2 billion. JGS said that the dramatic fall in consolidated net income was due to the 9% drop in the value of the Philippine Peso relative to the US Dollar, which had a negative impact on the value of JGS’s US Dollar-denominated debt. Of the five main business segments in the Gokongwei Family’s holdco, three were profitable and two were wildly unprofitable. Universal Robina [URC] reported a 28% increase in revenue and a 12% increase in net income, thanks to strong “sales momentum”. Robinsons Land [RLC] reported a 22% increase in revenue and a 21% increase in net income thanks to the recovery of malls and hotels, backed by strong residential sales. Robinsons Bank reported a 15% increase in revenue and a 12% increase in net income. On the negative side of things, Cebu Pacific [CEB] reported a 261% increase in revenue, but still reported a ₱14 billion net loss for FY22, due mostly to a 75% increase in operational expenses tied to the increase in the cost of fuel. JG Summit Olefins Corporation, the petrochemicals division, saw its revenues fall by 11% and it recorded a ₱14.9 billion net loss due to low demand from China and higher inputs.
  
  • MB: Depending on where you think global currencies are headed relative to the US Dollar, this either gives JGS an easy low bar that it will be able to dunk over this time next year when it reports on FY23, or it sounds an alarm about how exposed the JGS juggernaut is to moderate swings in the peso’s value. Of course, JGS didn’t talk about the phenomenon that evaporated 86% of its profitability until the third paragraph of this press release. It preferred to talk about the record revenues and the jump in core net income, which are definitely nicer stories to tell. Yet I couldn’t help but notice the repeated mention of rising input costs (for URC, CEB, and JGSOC) as factors that tempered profitability. That’s something to watch for as JGS navigates 2023. I don’t want to get distracted by JGS net income figures comparing to this year of forex losses, and perhaps miss some important inflation signals coming from its constituent businesses.
• [NOTES] Quick takes from around the market...
  
  • DMCI [DMC 11.66 ▼1.7%] [link] declared combined regular and special dividends of ₱0.72/share, payable on April 28 to DMC shareholders of record as of April 17. This brings the trailing 12 month dividend yield of DMC to 12.5% based on its pre-announcement closing price of ₱11.54/share. This year’s April dividend is 50% larger than what DMC paid-out in April 2021. The trailing 12 month dividend of ₱1.44/share represents 31% of DMC’s previous year’s core net income.
    • MB Quick Take: DMC is the parent company of Semirara Mining and Power [SCC 33.05 unch], which itself declared a fat FY22 dividend just a few days ago. That had members of the Dividend Club (no official membership, just people thirsty for passive income) politely losing their minds about what DMC could declare as a pass-through of SCC’s big div. Not bad.
  • Monde Nissin [MONDE 11.06 ▼1.6%] [link] teased FY22 net loss of ₱13 billion, which is 506% decrease from FY21’s net income of ₱3.2 billion. MONDE said that it registered a “non-cash, non-operating impairment” of ₱20.5 billion in the value of the intangible assets relating to its alternative meat business. MONDE said that the impairment was due to “the application of a higher discount rate due to the prevailing higher interest rates and risk premiums, some margin compression, and rationalization of the trend in the meat alternative category”. Outside of this massive charge, MONDE’s revenues were up 6.5% and core net income attributable fell 19.6% to ₱6.6 billion.
    • MB Quick Take: Objectively, this is a disaster. Sure, MONDE’s traditionally-strong segments were still just as strong, but those are mature products in mature industries that are simply not going to supply the kind of growth that can make up for such a massive write-down. When MONDE talks about “impairment”, what it is really doing is just adjusting the value of the alternative meat section to more closely resemble “fair market value”, and the net difference is passed through the income statement. The most troubling part of all of this is the line “rationalization of the trend in the alternative meat category.” As Market Babbler on Twitter pointed out, Quorn is “B1T1” (buy one take one) at S&R right now. “Rationalization” is just a fluffy way of saying that MONDE needed to finally get realistic about Quorn’s value. Unless MONDE can all of a sudden figure out a way to deliver proteins that are cheaper than organic proteins, the inflationary pressures on food and Quorn will continue to discourage customers from spending more to try alternative meat options.
  • Union Bank [UBP 85.00 ▼0.2%] [link] board voted to increase the bank’s PHP bonds program from ₱39 billion to ₱50 billion, a 28% increase. The board also voted to authorize the sale of ₱30 billion in bonds from the bonds program, but did not provide any additional information in terms of timeline for the sale or the intended use of proceeds for the money that will be raised.
    • MB Quick Take: More. More! MORE! UBP can’t seem to get enough capital to do all the things it wants to do. The banking sector is going through a bit of a consolidation phase right now, which means that the larger players are out shopping to buy up smaller players, so maybe UBP is cashing up to go hunting? The activity hasn’t translated directly into stock price performance yet, as UBP’s stock price is essentially flat with where it was before it announced its first SRO back in April of 2022. In that time the price has gone 16% lower and 13% higher than that level. MB is written and distributed every trading day. The newsletter is 100% free and I never upsell you to some "iNnEr cIrClE" of paid-membership perks. Everyone gets the same! Join the barkada by signing up for the newsletter, or follow me on Twitter. You can also read my daily Morning Halo-halo content on Philstar.com in the Stock Commentary section, and in the Saturday edition of the Daily Manila Shimbun. #Subscribe here #Read today's full newsletter here

• * Current credit cards you are the primary account holder of: no active cards, only a HELOC with a credit union that dosent offer a cashback card
• * FICO Scores with source (see note on FICO score sources below): 701 (from wells fargo website as we have a mortgage with them so they report changes online for me. 694 at the beginning of the year, 701 as of Feb.)
• * Number of personal credit cards approved for in the past 6 months: 0
• * Number of personal credit cards approved for in the past 12 months: 0
• * Number of personal credit cards approved for in the past 24 months:0
• * Annual income $: 65,000

• * OK with category-specific cards?: No
• * OK with rotating category cards?: not really but if 5/6% on rotating categories I will use heavily then maybe
• * Estimate average monthly spend in the categories below. Only include what you can pay by credit card.
  • * Dining $: 300
  • * Groceries $: Primarily Aldis and walmart - 250
  • * Gas $: Only Shell - 100
  • * Travel $: Dont travel at all. Occaisional emergency Lyft
  • * Do you plan on using this card abroad for a significant length of time (study abroad, digital nomad, expat, extended travel)?: No
  • * Any other categories (examples: phone/internet, insurance) or stores (example: Amazon) with significant, regular credit card spend (the more you specify, the better): $ Biggest spend every month, Utilites and internet total about $1,000.00, want that on a big cashback card.
  • * Any other significant, regular credit card spend you didn't include above?: No
  • * Can you pay rent by credit card? If yes, list rent amount and if there's a fee for paying by credit card: no

• * Current member of Amazon Prime?: yes
• * Current Verizon postpaid customer?:no
• * Current member of Costco or Sam's Club?no
• * Currently paying $13.99/month or more for Disney Bundle (Disney+ / Hulu / EPSN+) or other Hulu services? yes
• * Current member of Chase, US Bank or any other big bank?: Truist,
• * Active US military?:no
• * Are you open to Business Cards?:yes

• * What's the purpose of your next card (choose ONE)?: Cashback
  
  • * If you answered "first credit card", are you an authorized user on any other cards? no

The intelligence environment has been significantly changed over recent years by many factors, including tech-savvy threat actors, the rapid spread of online communications, increased societal unrest and changing geopolitical dynamics. Government and corporate sectors alike are facing an increasing volume and diversity of threats to their communities and businesses.
These threats, combined with masses of data from exploding numbers of online platforms, create a perfect storm of challenges for intelligence teams. As the threat landscape evolves, the technology used to uncover these threats must also evolve - that is where advanced open-source intelligence (OSINT) solutions play an increasingly critical role. Open-source intelligence, often referred to as a subset of digital intelligence, is the process of collecting, analyzing, and extracting meaningful insights from publicly available data sources, including social media, news feeds, blog sites, discussion forums, and more. Terrorist groups, human trafficking networks, politically motivated extremist groups, and other criminals and threat actors are radicalizing, advertising, recruiting, and planning across a constantly evolving range of websites and social media platforms across the Surface, Deep and Dark Web, often communicating in ways that make it difficult for intelligence and law enforcement organizations to monitor their activities and understand the nature of these threats at any given moment.
The sheer volume and complexity of data presents significant challenges - monitoring online platforms and uncovering critical insights is beyond human scale and any attempt to simplify masses of data looking for anything interesting will inevitably lead to false positives and (worse still) operator burnout. This is driving a need for the advanced, AI-enabled insights into masses of online data that open-source intelligence technology delivers.
OSINT is emerging as an invaluable primary intelligence source across law enforcement, intelligence, defense, security vetting, and corporate agencies worldwide. To showcase best practices for applying OSINT to some of the world’s biggest challenges, this section explores several key use cases: — violent extremist threat monitoring, — security vetting/insider threat, — assistance to law enforcement and — corporate supply chain protection
…meme culture is where AI-enabled risk analytics prove to be invaluable in interpreting threats that appear in the form of images, videos, written text, or digital network connections. For example, Fivecast OSINT solutions have been proven to save analyst teams hours and days of manual data manipulation with ongoing, repeatable, and automated collection and assessment of these diverse data mediums, presented in a way that makes assessment efficient. The customizable risk detection framework rapidly surfaces content of interest, including user-defined keywords, phrases, and quotes in posts, while automatically assessing images and videos for objects, memes, concepts, logos, and text (extracted through optical character recognition) of interest.
…as specialist OSINT companies move into this space, with tailored products to keep pace with the vetting, revalidation, and now continuous vetting requirements of governments and corporates, the interest in online data for vetting and insider threat use cases is steadily growing.
Continuous vetting is the ongoing, “light-touch” monitoring of security clearance holders, a considered move away from the flawed paradigm of assessing a security clearance at intervals of five and ten years. Although still in its conceptual phase in Australia, the United States is moving ahead at pace.
In October 2021, William Lietzau, the Director of the Defense Counterintelligence and Security Agency, said approximately 4 million defense personnel, including military, civilians and contractors, are subject to their continuous vetting program, which is part of the agency’s Trusted Workforce 2.0 initiative and security clearance process.
…If Alshamrani’s (a person accused of terrorism) account had been continuously monitored, it is likely his online activity would have alerted defense vetting agencies well before the attack took place.
OSINT is well established as a source of intelligence in law enforcement, both within Australian and partner agencies overseas. In part, this early formalization of OSINT as a primary intelligence source was necessary due to the “Going Dark” phenomenon. Going Dark was a term first coined in 2015 by then Federal Bureau of Investigation Director James Comey to describe the effect of major telecommunications providers – device manufacturers and app developers alike – enabling end-toend encryption by default across their product ranges. The effect was to freeze out (almost totally) telecommunications intercept, the ‘wiretap’ capability, and digital forensics, the capability to ‘crack’ devices in use by criminals.
Without this baseload data collection, law enforcement rapidly pivoted to alternatives, implementing strong collection and assessment of publicly available online data to provide that broad awareness of the criminal milieu so critical to effective investigations …: OSINT directly assists surveillance by building out a target’s pattern of life prior to a team deploying in the field offering critical insights such as networks of likely social interactions, frequented locations, propensity for violence, or access to weapons. The same can be said in support of human source recruitment and management, where OSINT can be used to passively observe any changes in the interactions, motivations, and activities of an individual that may be of concern to their case officehandler.
…The ANOM app: instead of providing secure communication, it was actually a trojan horse covertly distributed by the United States Federal Bureau of Investigation (FBI) and the Australian Federal Police (AFP), enabling them to monitor all communications.

Fivecast was tasked to seek out supply chain risk for a global corporate in vehicle manufacturing.
By examining the company’s various subsidiaries’ official presence across three key social media platforms, analysts were able to quickly establish that protest activity was occurring against one of their manufacturing plants in Germany. Although, at the surface level, this protest activity appeared to be organized by a local trade union, Fivecast was able to establish a deeper underlying motivation by exploring the online activity of the key news agency promoting this protest activity – Rote Fahne News, the news arm of the Marxist-Leninist party of Germany. From a broad brief to discover supply chain risk across a broad portfolio, OSINT was able to establish the threat, its location, and its underlying motivation
Previously the domain of well-managed telecommunications intercept, which has all but “gone dark”, enterprise-level OSINT systems are the obvious replacement to fill that data collection gap. OSINT will become the backbone for data collection on which investigations are built. Rapidly scalable, automated, high reliability, cloud-hosted OSINT systems able to reach online data anywhere (from anywhere) will capture the digital patterns of life of an individual out to 1000s of persons of interest at once.
Machine Learning is a current application of AI-based around the idea that we should really just be able to give machines access to data and let them learn for themselves. A simple way that Fivecast defines AI/ML in OSINT is any capability informed by a model that is “trained”. In this regard, there are a range of capabilities available in advanced OSINT tools now:
— Image detection and classification (including facial recognition) – searches of complete and partial images against mass datasets to return high accuracy matches. — Automated person of interest resolution – taking basic biodata of an entity/entities, finding new data and resolving it to those entities with high accuracy. — Logo detection – recognizing simple and complex (e.g. on clothing) logos in images. — Sentiment and emotion – detection and assessment of sentiment (positive/negative) and key emotions (anger, disgust, fear, joy, sadness) in text. — Text similarity – understanding the content and context of passages of text and finding similar meanings in other text (e.g. identifying threats of violence).
These capabilities are all loosely clustered around sifting and sorting functions – how to make the data haystack as manageable as possible for analysts and investigators. In the coming five years, we will very likely see a transition in the focus of the AI/ML from assistance to decision-making. The size of the data haystack is already well beyond human scale, regardless of your intelligence mission. Perhaps discomforting for some, but that point is approaching where the volume (and complexity) of final decision making will be too much - OSINT tools become so good at finding what the intelligence user demands that the tool must also make increasingly complex decisions on what to do with that data output.

Computer vision is a field of artificial intelligence that trains computers to interpret and understand the visual world. Using digital images from cameras and videos and deep learning models, machines can accurately identify and classify objects — and then react to what they “see.”
Data-driven organizations across all industries are unlocking actionable intelligence from real-time video data coupled with other edge sensor data like audio and biometrics, artificial intelligence (AI), and high-performance edge computing. Adding stored historical data enables a powerful method of using deep learning techniques on videos and digital images known as computer vision, and it’s not only transforming organizations, but more importantly, it’s changing how they build or deliver a product or service. According to IDC, forward-looking organizations that maximize their data to generate insights are two times more profitable and see eight times more growth than their peers.
Computer vision capabilities are fast becoming a significant contributor to that end. Analysts at Omdia expect the global computer vision software market to reach $33.5 billion by 2025 (growing at 42.1 percent year over year). Connecting computer vision to the edge directly impacts what customers do to drive revenue in their organizations. Whether it’s gaining a greater knowledge of customer behavior within a retail space, predicting failures in oil and gas pipelines, controlling autonomous vehicles in a smart city, or managing traveler flow in an airport, private and public organizations of all sizes are capitalizing on the petabytes of audio-visual data captured daily
Historical data can be used as a training archive to develop increasingly accurate models for compelling insights.
government agencies need real-time monitoring at public events or for agriculture, construction, or mining organizations requiring immediate response to system failures in the field
An agile edge-to-core computer vision platform and framework allow cognitive insights to be generated close to the data sources and saved for later use The addition of new systems designed to enhance protection can actually add security gaps and holes if they are not well integrated.
…an environment susceptible to ‘monitoring fatigue’.

Information technology and telecom, energy, banking and finance, transportation and border security, water, and emergency services. These critical infrastructures share a common threat of vandalism, theft and attack coupled with concerns for regulatory compliance and the liability associated with trespassing. By adding advanced perimeter security solutions, these sites can detect intruders before they breach the perimeter.
Radar detection solutions that warn of fast-approaching vehicles coupled with license plate recognition solutions can provide both advanced warning of an imminent threat and the analytics to quickly react to and mitigate potentially dangerous situations. AI-powered heat mapping and behavior analysis tools can also amplify a security team’s ability to proactively assess threats through crowd-gather alerts, wrong-way travel, and other data-driven information.
Milestone revolutionized the industry by leading the transformation from analog to IP cameras. The transformation set the stage for modern video surveillance technology. In 2014, Canon acquired Milestone…By 2019, our net revenue reached just over 143 million USD…by 2022, 215 million USD. …Today, we are present in 25 countries and with partners and customers in nearly every corner of the world.
Data-driven video technology increases the value of video streams—traditionally utilized for safety and security purposes—by combining Artificial Intelligence (AI) with video technology. For example, by adding Artificial Intelligence to the mix, we are getting things like Adaptive Video Analytics, which allow users to calibrate the AI model deployed at various sites. In practice, this means that the industry will continue to move towards embedding self-learning, self-calibrating video analytic technology into cameras and other devices, allowing them to self-adjust to changing scene conditions. All that data will be captured by the Video Management Software (VMS). In the future, this data will improve the accuracy of Video Analytics and make the value of the video streams captured, organized, and archived by the VMS incredibly important. Data-driven video technology will truly “make the world see.”
Threats, unlike any previously imagined have become real and commonplace
Preventing access to physical machines and networking using biometric credentials is in keeping with a broader industry trend to phase out easily compromised techniques such as passwords and pins.
Security no longer involves simply physical access; it now must embrace digital access and the authorization to execute transactions and services using personal devices. Examples include leveraging biometrics built into mobile devices such as mobile phones and electronic wearables to provide real-time requests for authorization to complete transactions, access systems, or to move data. Electronic objects and networks which may be connected and accessed using personal electronics include:

In the world of digital security these are all considered “connected objects.” Biometric solutions play a mission critical role in the new world of “connected objects” to provide verification and trust (certainty) of an individual’s identity for frictionless, secure physical and digital access. Biometrics provides assurance that only an authorized individual can access their “connected objects.”

2023 will see significant adoption of AI-based analytics in cameras and video management systems (VMS) as more manufacturers provide this feature within their standard camera lines. There are simply too many camera streams for humans to monitor effectively, so AI-based analytics will be a catalyst that enables security departments to do more with less.
Video surveillance for education must integrate easily with other security applications to extend the power of the system.
...ditching manual methods once and for all.
Successful businesses are preparing their operations for the future and want a video surveillance system that is AI capable and has the flexibility to run advanced analytics. Dynamic shifts over the past few years in the way the world does business forced companies to use technology in new ways. Video surveillance systems, once only used for security, are now a tool to help optimize business operations. Businesses want an AI-ready video surveillance system that will generate useful insights from gathered data.
Over 50% of businesses are using AI in some way, with more than 25% reporting widespread AI adoption within their company, according to a 2022 AI business survey by PriceWaterhouseCoopers. The survey shows that businesses that are not already using AI know that new, modern technologies will automate their systems and processes in the future and are budgeting for the infrastructure now.
Video surveillance systems capable of running AI help businesses scale their ability to analyze and act on data. Advanced uses include systems that can automatically detect and send real-time alerts of security threats and gather data to provide useful information like peak foot traffic or customer wait times.
In 2022 inflation broke a 40-year high. There are few indications that consumers or businesses can expect inflation relief in the cost of goods and services in the near future. Security companies must find ways to increase revenue to compensate for the higher prices in materials, overhead increases, wage inflation, and the possible attrition of customers who need to “tighten the belt.”
According to the National Apartment Association (NAA), demand for apartments is at an all-time high. The demand is driven by a number of young adults aged 18 to 24 who are delaying home ownership and an aging population sometimes choosing to live in apartments.
Parks Associates research finds that 80% of property managers plan to implement smart home devices within the next 12 months, demonstrating a strong demand for automation and operational efficiency in the MDU space (living in an apartment with a roommate, basically).
Whether for a video doorbell or freestanding camera, manufacturers are improving pixel quality, night vision, thermal vision, camera view, camera durability, battery life, and A.I. detecting capabilities.
adoption of vehicle monitoring services is on the rise
almost 50% of apartment or townhome residents report having a package theft, while over 60% of condominium residents report having a package stolen.
Overall, Swiftlane estimates $6 billion worth of packages were stolen in 2020.
Frictionless Technology Keeps Gaining Momentum
Before the pandemic, the market was moving toward frictionless options, but COVID accelerated the need for touch-free technology. Today, the frictionless user experience is here to stay, the company says, because it delivers highly secure access using biometric identifiers that are unique to each individual, have greater ease of use, and can reduce the spread of germs.
The three primary technologies used to create a frictionless experience are iris scans, facial recognition and facial authentication. Iris scans have proven to help boost security, but adoption has lagged, given the disruption it creates for movement into secure areas. Facial recognition, primarily used in mass surveillance, has shown promise, but privacy concerns have slowed adoption.
And, with the introduction of facial authentication in everyday consumer products such as the iPhone, it is becoming the go-to technology to create a frictionless environment
When facial authentication is coupled with intelligent systems, not only can someone receive real-time security alerts when unauthorized access to restricted entrances occurs, but they also get actionable data to modify user behavior.
The security industry is innovating rapidly to provide new solutions that drive revenue and customer loyalty. Product features that are cutting edge today will be expected features in base model products. Dealers need to keep abreast of the latest innovations to source products that customers will start to demand
The impact on security dealers looks to be a net positive, as the major players in the home security space are currently seeing record highs in revenue despite slowed growth and times of economic uncertainty.

The intelligence environment has been significantly changed over recent years by many factors, including tech-savvy threat actors, the rapid spread of online communications, increased societal unrest and changing geopolitical dynamics. Government and corporate sectors alike are facing an increasing volume and diversity of threats to their communities and businesses.
These threats, combined with masses of data from exploding numbers of online platforms, create a perfect storm of challenges for intelligence teams. As the threat landscape evolves, the technology used to uncover these threats must also evolve - that is where advanced open-source intelligence (OSINT) solutions play an increasingly critical role. Open-source intelligence, often referred to as a subset of digital intelligence, is the process of collecting, analyzing, and extracting meaningful insights from publicly available data sources, including social media, news feeds, blog sites, discussion forums, and more. Terrorist groups, human trafficking networks, politically motivated extremist groups, and other criminals and threat actors are radicalizing, advertising, recruiting, and planning across a constantly evolving range of websites and social media platforms across the Surface, Deep and Dark Web, often communicating in ways that make it difficult for intelligence and law enforcement organizations to monitor their activities and understand the nature of these threats at any given moment.
The sheer volume and complexity of data presents significant challenges - monitoring online platforms and uncovering critical insights is beyond human scale and any attempt to simplify masses of data looking for anything interesting will inevitably lead to false positives and (worse still) operator burnout. This is driving a need for the advanced, AI-enabled insights into masses of online data that open-source intelligence technology delivers.
OSINT is emerging as an invaluable primary intelligence source across law enforcement, intelligence, defense, security vetting, and corporate agencies worldwide. To showcase best practices for applying OSINT to some of the world’s biggest challenges, this section explores several key use cases: — violent extremist threat monitoring, — security vetting/insider threat, — assistance to law enforcement and — corporate supply chain protection
…meme culture is where AI-enabled risk analytics prove to be invaluable in interpreting threats that appear in the form of images, videos, written text, or digital network connections. For example, Fivecast OSINT solutions have been proven to save analyst teams hours and days of manual data manipulation with ongoing, repeatable, and automated collection and assessment of these diverse data mediums, presented in a way that makes assessment efficient. The customizable risk detection framework rapidly surfaces content of interest, including user-defined keywords, phrases, and quotes in posts, while automatically assessing images and videos for objects, memes, concepts, logos, and text (extracted through optical character recognition) of interest.
…as specialist OSINT companies move into this space, with tailored products to keep pace with the vetting, revalidation, and now continuous vetting requirements of governments and corporates, the interest in online data for vetting and insider threat use cases is steadily growing.
Continuous vetting is the ongoing, “light-touch” monitoring of security clearance holders, a considered move away from the flawed paradigm of assessing a security clearance at intervals of five and ten years. Although still in its conceptual phase in Australia, the United States is moving ahead at pace.
In October 2021, William Lietzau, the Director of the Defense Counterintelligence and Security Agency, said approximately 4 million defense personnel, including military, civilians and contractors, are subject to their continuous vetting program, which is part of the agency’s Trusted Workforce 2.0 initiative and security clearance process.
…If Alshamrani’s (a person accused of terrorism) account had been continuously monitored, it is likely his online activity would have alerted defense vetting agencies well before the attack took place.
OSINT is well established as a source of intelligence in law enforcement, both within Australian and partner agencies overseas. In part, this early formalization of OSINT as a primary intelligence source was necessary due to the “Going Dark” phenomenon. Going Dark was a term first coined in 2015 by then Federal Bureau of Investigation Director James Comey to describe the effect of major telecommunications providers – device manufacturers and app developers alike – enabling end-toend encryption by default across their product ranges. The effect was to freeze out (almost totally) telecommunications intercept, the ‘wiretap’ capability, and digital forensics, the capability to ‘crack’ devices in use by criminals.
Without this baseload data collection, law enforcement rapidly pivoted to alternatives, implementing strong collection and assessment of publicly available online data to provide that broad awareness of the criminal milieu so critical to effective investigations …: OSINT directly assists surveillance by building out a target’s pattern of life prior to a team deploying in the field offering critical insights such as networks of likely social interactions, frequented locations, propensity for violence, or access to weapons. The same can be said in support of human source recruitment and management, where OSINT can be used to passively observe any changes in the interactions, motivations, and activities of an individual that may be of concern to their case officehandler.
…The ANOM app: instead of providing secure communication, it was actually a trojan horse covertly distributed by the United States Federal Bureau of Investigation (FBI) and the Australian Federal Police (AFP), enabling them to monitor all communications.

Fivecast was tasked to seek out supply chain risk for a global corporate in vehicle manufacturing.
By examining the company’s various subsidiaries’ official presence across three key social media platforms, analysts were able to quickly establish that protest activity was occurring against one of their manufacturing plants in Germany. Although, at the surface level, this protest activity appeared to be organized by a local trade union, Fivecast was able to establish a deeper underlying motivation by exploring the online activity of the key news agency promoting this protest activity – Rote Fahne News, the news arm of the Marxist-Leninist party of Germany. From a broad brief to discover supply chain risk across a broad portfolio, OSINT was able to establish the threat, its location, and its underlying motivation
Previously the domain of well-managed telecommunications intercept, which has all but “gone dark”, enterprise-level OSINT systems are the obvious replacement to fill that data collection gap. OSINT will become the backbone for data collection on which investigations are built. Rapidly scalable, automated, high reliability, cloud-hosted OSINT systems able to reach online data anywhere (from anywhere) will capture the digital patterns of life of an individual out to 1000s of persons of interest at once.
Machine Learning is a current application of AI-based around the idea that we should really just be able to give machines access to data and let them learn for themselves. A simple way that Fivecast defines AI/ML in OSINT is any capability informed by a model that is “trained”. In this regard, there are a range of capabilities available in advanced OSINT tools now:
— Image detection and classification (including facial recognition) – searches of complete and partial images against mass datasets to return high accuracy matches. — Automated person of interest resolution – taking basic biodata of an entity/entities, finding new data and resolving it to those entities with high accuracy. — Logo detection – recognizing simple and complex (e.g. on clothing) logos in images. — Sentiment and emotion – detection and assessment of sentiment (positive/negative) and key emotions (anger, disgust, fear, joy, sadness) in text. — Text similarity – understanding the content and context of passages of text and finding similar meanings in other text (e.g. identifying threats of violence).
These capabilities are all loosely clustered around sifting and sorting functions – how to make the data haystack as manageable as possible for analysts and investigators. In the coming five years, we will very likely see a transition in the focus of the AI/ML from assistance to decision-making. The size of the data haystack is already well beyond human scale, regardless of your intelligence mission. Perhaps discomforting for some, but that point is approaching where the volume (and complexity) of final decision making will be too much - OSINT tools become so good at finding what the intelligence user demands that the tool must also make increasingly complex decisions on what to do with that data output.

Computer vision is a field of artificial intelligence that trains computers to interpret and understand the visual world. Using digital images from cameras and videos and deep learning models, machines can accurately identify and classify objects — and then react to what they “see.”
Data-driven organizations across all industries are unlocking actionable intelligence from real-time video data coupled with other edge sensor data like audio and biometrics, artificial intelligence (AI), and high-performance edge computing. Adding stored historical data enables a powerful method of using deep learning techniques on videos and digital images known as computer vision, and it’s not only transforming organizations, but more importantly, it’s changing how they build or deliver a product or service. According to IDC, forward-looking organizations that maximize their data to generate insights are two times more profitable and see eight times more growth than their peers.
Computer vision capabilities are fast becoming a significant contributor to that end. Analysts at Omdia expect the global computer vision software market to reach $33.5 billion by 2025 (growing at 42.1 percent year over year). Connecting computer vision to the edge directly impacts what customers do to drive revenue in their organizations. Whether it’s gaining a greater knowledge of customer behavior within a retail space, predicting failures in oil and gas pipelines, controlling autonomous vehicles in a smart city, or managing traveler flow in an airport, private and public organizations of all sizes are capitalizing on the petabytes of audio-visual data captured daily
Historical data can be used as a training archive to develop increasingly accurate models for compelling insights.
government agencies need real-time monitoring at public events or for agriculture, construction, or mining organizations requiring immediate response to system failures in the field
An agile edge-to-core computer vision platform and framework allow cognitive insights to be generated close to the data sources and saved for later use The addition of new systems designed to enhance protection can actually add security gaps and holes if they are not well integrated.
…an environment susceptible to ‘monitoring fatigue’.

Information technology and telecom, energy, banking and finance, transportation and border security, water, and emergency services. These critical infrastructures share a common threat of vandalism, theft and attack coupled with concerns for regulatory compliance and the liability associated with trespassing. By adding advanced perimeter security solutions, these sites can detect intruders before they breach the perimeter.
Radar detection solutions that warn of fast-approaching vehicles coupled with license plate recognition solutions can provide both advanced warning of an imminent threat and the analytics to quickly react to and mitigate potentially dangerous situations. AI-powered heat mapping and behavior analysis tools can also amplify a security team’s ability to proactively assess threats through crowd-gather alerts, wrong-way travel, and other data-driven information.
Milestone revolutionized the industry by leading the transformation from analog to IP cameras. The transformation set the stage for modern video surveillance technology. In 2014, Canon acquired Milestone…By 2019, our net revenue reached just over 143 million USD…by 2022, 215 million USD. …Today, we are present in 25 countries and with partners and customers in nearly every corner of the world.
Data-driven video technology increases the value of video streams—traditionally utilized for safety and security purposes—by combining Artificial Intelligence (AI) with video technology. For example, by adding Artificial Intelligence to the mix, we are getting things like Adaptive Video Analytics, which allow users to calibrate the AI model deployed at various sites. In practice, this means that the industry will continue to move towards embedding self-learning, self-calibrating video analytic technology into cameras and other devices, allowing them to self-adjust to changing scene conditions. All that data will be captured by the Video Management Software (VMS). In the future, this data will improve the accuracy of Video Analytics and make the value of the video streams captured, organized, and archived by the VMS incredibly important. Data-driven video technology will truly “make the world see.”
Threats, unlike any previously imagined have become real and commonplace
Preventing access to physical machines and networking using biometric credentials is in keeping with a broader industry trend to phase out easily compromised techniques such as passwords and pins.
Security no longer involves simply physical access; it now must embrace digital access and the authorization to execute transactions and services using personal devices. Examples include leveraging biometrics built into mobile devices such as mobile phones and electronic wearables to provide real-time requests for authorization to complete transactions, access systems, or to move data. Electronic objects and networks which may be connected and accessed using personal electronics include:

In the world of digital security these are all considered “connected objects.” Biometric solutions play a mission critical role in the new world of “connected objects” to provide verification and trust (certainty) of an individual’s identity for frictionless, secure physical and digital access. Biometrics provides assurance that only an authorized individual can access their “connected objects.”

2023 will see significant adoption of AI-based analytics in cameras and video management systems (VMS) as more manufacturers provide this feature within their standard camera lines. There are simply too many camera streams for humans to monitor effectively, so AI-based analytics will be a catalyst that enables security departments to do more with less.
Video surveillance for education must integrate easily with other security applications to extend the power of the system.
...ditching manual methods once and for all.
Successful businesses are preparing their operations for the future and want a video surveillance system that is AI capable and has the flexibility to run advanced analytics. Dynamic shifts over the past few years in the way the world does business forced companies to use technology in new ways. Video surveillance systems, once only used for security, are now a tool to help optimize business operations. Businesses want an AI-ready video surveillance system that will generate useful insights from gathered data.
Over 50% of businesses are using AI in some way, with more than 25% reporting widespread AI adoption within their company, according to a 2022 AI business survey by PriceWaterhouseCoopers. The survey shows that businesses that are not already using AI know that new, modern technologies will automate their systems and processes in the future and are budgeting for the infrastructure now.
Video surveillance systems capable of running AI help businesses scale their ability to analyze and act on data. Advanced uses include systems that can automatically detect and send real-time alerts of security threats and gather data to provide useful information like peak foot traffic or customer wait times.
In 2022 inflation broke a 40-year high. There are few indications that consumers or businesses can expect inflation relief in the cost of goods and services in the near future. Security companies must find ways to increase revenue to compensate for the higher prices in materials, overhead increases, wage inflation, and the possible attrition of customers who need to “tighten the belt.”
According to the National Apartment Association (NAA), demand for apartments is at an all-time high. The demand is driven by a number of young adults aged 18 to 24 who are delaying home ownership and an aging population sometimes choosing to live in apartments.
Parks Associates research finds that 80% of property managers plan to implement smart home devices within the next 12 months, demonstrating a strong demand for automation and operational efficiency in the MDU space (living in an apartment with a roommate, basically).
Whether for a video doorbell or freestanding camera, manufacturers are improving pixel quality, night vision, thermal vision, camera view, camera durability, battery life, and A.I. detecting capabilities.
adoption of vehicle monitoring services is on the rise
almost 50% of apartment or townhome residents report having a package theft, while over 60% of condominium residents report having a package stolen.
Overall, Swiftlane estimates $6 billion worth of packages were stolen in 2020.
Frictionless Technology Keeps Gaining Momentum
Before the pandemic, the market was moving toward frictionless options, but COVID accelerated the need for touch-free technology. Today, the frictionless user experience is here to stay, the company says, because it delivers highly secure access using biometric identifiers that are unique to each individual, have greater ease of use, and can reduce the spread of germs.
The three primary technologies used to create a frictionless experience are iris scans, facial recognition and facial authentication. Iris scans have proven to help boost security, but adoption has lagged, given the disruption it creates for movement into secure areas. Facial recognition, primarily used in mass surveillance, has shown promise, but privacy concerns have slowed adoption.
And, with the introduction of facial authentication in everyday consumer products such as the iPhone, it is becoming the go-to technology to create a frictionless environment
When facial authentication is coupled with intelligent systems, not only can someone receive real-time security alerts when unauthorized access to restricted entrances occurs, but they also get actionable data to modify user behavior.
The security industry is innovating rapidly to provide new solutions that drive revenue and customer loyalty. Product features that are cutting edge today will be expected features in base model products. Dealers need to keep abreast of the latest innovations to source products that customers will start to demand
The impact on security dealers looks to be a net positive, as the major players in the home security space are currently seeing record highs in revenue despite slowed growth and times of economic uncertainty.

1. Real Time Notifications-

1. Kill-Mode Feature

1. PIN Protected Lock

1. Cost Friendly

1. Designed to Work as Long-term Solution

1. What makes Baigan Box Stand out?

Company Description

• Fashion & Leather goods: 49% (20%)
• Selective retailing and other activities: 19% (17%)
• Watches & Jewelry: 13% (12%)
• Perfumes & Cosmetics: 10% (10%)
• Wines & Spirits: 9% (11%)

• Asia: 37%
• United States: 27%
• Europe: 24%
• Other Markets: 12%

Valuation (Discounted Cash Flow)

• Revenue growth rate for the next 5 years will be 9% decreasing slowly from the year 6 to 10 to the risk-free rate.
• Operating Margin: The operating margin is forecasted to rise from 26.54% in 2022 to 28.5% in 2027, due to increasing efficiency and pricing power.
• Cost of Capital: The company's cost of capital stands at 7.27%, with 92.81% of it being equity with a cost of 7.63%, and 7.19% being debt with a cost of debt of 2.61%.
• Terminal Growth Rate: The terminal growth rate is anticipated to be the risk-free rate of 2.50%.
• Terminal Cost of Capital: The terminal cost of capital is calculated as the risk-free rate plus 4.5%, equating to 7%.
• Terminal Return on Invested Capital: The terminal return on invested capital is expected to be 13%.
• Value per Share: The value per share is estimated to be €747.
• Market Price Today: The current market price of the company is €817.

• Market Price Today Dior: The current market price of the company is €793.
• Value per Share: The value per share of Dior is estimated to be €747*1.14 = €852

Benjamin Graham Valuation Model

• Earnings per share in period 0: €28.03
• Growth in EPS in the next 7 to 10 years: 9%
• Current Yield on AAA Corporate bonds: 4%
• Value of the stock according to the model: €817.

Risks

• LVMH does not hedge their currency risk. 80% of their revenues are in foreign currencies while only 20% are in €, but most of their costs are in € which can be a risk. LVMH is able to offset the currency headwinds through price increases for certain brands where demand is strong.

• While the company’s overall record of mergers and acquisitions is quite successful, remains a risk of overpaying or choosing a target poorly. Acquisitions can also drag the group into less profitable and more competitive businesses.

TLDR

Relevant News:

Company Description

• Fashion & Leather goods: 49% (20%)
• Selective retailing and other activities: 19% (17%)
• Watches & Jewelry: 13% (12%)
• Perfumes & Cosmetics: 10% (10%)
• Wines & Spirits: 9% (11%)

• Asia: 37%
• United States: 27%
• Europe: 24%
• Other Markets: 12%

Valuation (Discounted Cash Flow)

• Revenue growth rate for the next 5 years will be 9% decreasing slowly from the year 6 to 10 to the risk-free rate.
• Operating Margin: The operating margin is forecasted to rise from 26.54% in 2022 to 28.5% in 2027, due to increasing efficiency and pricing power.
• Cost of Capital: The company's cost of capital stands at 7.27%, with 92.81% of it being equity with a cost of 7.63%, and 7.19% being debt with a cost of debt of 2.61%.
• Terminal Growth Rate: The terminal growth rate is anticipated to be the risk-free rate of 2.50%.
• Terminal Cost of Capital: The terminal cost of capital is calculated as the risk-free rate plus 4.5%, equating to 7%.
• Terminal Return on Invested Capital: The terminal return on invested capital is expected to be 13%.
• Value per Share: The value per share is estimated to be €747.
• Market Price Today: The current market price of the company is €817.

• Market Price Today Dior: The current market price of the company is €793.
• Value per Share: The value per share of Dior is estimated to be €747*1.14 = €852

Benjamin Graham Valuation Model

• Earnings per share in period 0: €28.03
• Growth in EPS in the next 7 to 10 years: 9%
• Current Yield on AAA Corporate bonds: 4%
• Value of the stock according to the model: €817.

Risks

• LVMH does not hedge their currency risk. 80% of their revenues are in foreign currencies while only 20% are in €, but most of their costs are in € which can be a risk. LVMH is able to offset the currency headwinds through price increases for certain brands where demand is strong.

• While the company’s overall record of mergers and acquisitions is quite successful, remains a risk of overpaying or choosing a target poorly. Acquisitions can also drag the group into less profitable and more competitive businesses.

TLDR

Relevant News: