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In our previous discussion, we introduced the MinIO Object Store Firewall, a novel security component that goes beyond traditional network and application security layers. Neither IP-based firewalls nor application firewalls are designed for data. That is why we built the MinIO Enterprise Object Store Firewall – because in the modern enterprise, data is what must be protected and an S3-aware firewall doesn’t exist. This S3-aware data firewall is crucial for modern data protection, operating at the storage layer to safeguard your data comprehensively. The MinIO Enterprise Object Store Firewall is designed specifically to work with applications using MinIO object store and its API endpoints. The Enterprise Firewall is lightweight, powerful, flexible and extensible. Let’s delve into setting up this advanced firewall, designed to secure your data in today’s increasingly complex digital landscape. Enable and Configure Firewall Let's use the Enterprise Console to set up the firewall. Follow the below steps to enable and configure the Firewall. Configure TLS for Secure Communication As part of the MinIO Enterprise Suite, we’ve always recommended to ensure you enable TLS on MinIO Enterprise Object Store so that even inter cluster communications are encrypted. With that same spirit, we support TLS for the Enterprise Firewall as well. This ensures that any connection to the MinIO Object Store via the Firewall is encrypted end to end. For enhanced security, configure TLS settings when launching the firewall with Let’s Encrypt. Precedence of Anonymous Rule In our MinIO Enterprise Firewall configuration, you’ll encounter two distinct rules for anonymous access: Global Anonymous Setting: At the start when you enable firewall, we specify a global setting that allows anonymous access across all buckets unless a more specific rule denies it. Bucket Specific Anonymous: After configuring the global setting, under each individual rules, we can set a more specific rule that overrides the global setting, effectively denying anonymous access In this case, even though we initially toggled Global Anonymous to Allow for all buckets, because we set another more specific rule below it, which also applies to all buckets, the one we set later takes precedence over the global setting. In other words, anonymous bucket access will be denied for all buckets. Load Balance across MinIO nodes As an added bonus, because we need to define all the MinIO nodes as a backend for the Firewall, the Firewall doubles as a LoadBalancer, negating the need for a separate load balancer between the firewall and MinIO nodes. This eliminates further complexity and ensures there is no single point of failure in case one of the MinIO backend goes offline. Please note, you need to have another level of redundancy to ensure when connecting to Enterprise Firewall the incoming connections are also distributed to multiple Enterprise Firewall instances. This configuration is beyond the scope of this blog but its something to keep in mind. Health Checks and Monitoring The health check enabled you to see if the Firewall is in a healthy state. You can check the health and liveliness as follows. If everything is Green that will indicate that the firewall is functioning properly. Final Thoughts With the MinIO Enterprise Firewall, gone are the days of wrestling with complex IPtables and unclear access policies.Our firewall solution simplifies your security by focusing exclusively on the essential rules required for your object store and API interactions. It is optimized to ensure there are no latency or unforeseen rules, blocking access to your MinIO object store. Moreover, the Enterprise Firewall is fully supported by our awesome team at SUBNET where we can help you by architecting the Enterprise Firewall the right way to work with MinIO object store and troubleshoot any future issues. So what are you waiting for? If you have any questions on MinIO Enterprise Object Store Firewall be sure to reach out to us on Slack or hello@min.io! In our previous discussion , we introduced the MinIO Object Store Firewall, a novel security component that goes beyond traditional network and application security layers. Neither IP-based firewalls nor application firewalls are designed for data. That is why we built the MinIO Enterprise Object Store Firewall – because in the modern enterprise, data is what must be protected and an S3-aware firewall doesn’t exist. This S3-aware data firewall is crucial for modern data protection, operating at the storage layer to safeguard your data comprehensively. previous discussion previous discussion The MinIO Enterprise Object Store Firewall is designed specifically to work with applications using MinIO object store and its API endpoints. The Enterprise Firewall is lightweight, powerful, flexible and extensible. Let’s delve into setting up this advanced firewall, designed to secure your data in today’s increasingly complex digital landscape. Enable and Configure Firewall Let's use the Enterprise Console to set up the firewall. Follow the below steps to enable and configure the Firewall. Configure TLS for Secure Communication As part of the MinIO Enterprise Suite, we’ve always recommended to ensure you enable TLS on MinIO Enterprise Object Store so that even inter cluster communications are encrypted. With that same spirit, we support TLS for the Enterprise Firewall as well. This ensures that any connection to the MinIO Object Store via the Firewall is encrypted end to end. For enhanced security, configure TLS settings when launching the firewall with Let’s Encrypt. Precedence of Anonymous Rule In our MinIO Enterprise Firewall configuration, you’ll encounter two distinct rules for anonymous access: Global Anonymous Setting: At the start when you enable firewall, we specify a global setting that allows anonymous access across all buckets unless a more specific rule denies it. Global Anonymous Setting: Bucket Specific Anonymous: After configuring the global setting, under each individual rules, we can set a more specific rule that overrides the global setting, effectively denying anonymous access Bucket Specific Anonymous: In this case, even though we initially toggled Global Anonymous to Allow for all buckets, because we set another more specific rule below it, which also applies to all buckets, the one we set later takes precedence over the global setting. In other words, anonymous bucket access will be denied for all buckets. Load Balance across MinIO nodes As an added bonus, because we need to define all the MinIO nodes as a backend for the Firewall, the Firewall doubles as a LoadBalancer, negating the need for a separate load balancer between the firewall and MinIO nodes. This eliminates further complexity and ensures there is no single point of failure in case one of the MinIO backend goes offline. Please note, you need to have another level of redundancy to ensure when connecting to Enterprise Firewall the incoming connections are also distributed to multiple Enterprise Firewall instances. This configuration is beyond the scope of this blog but its something to keep in mind. Health Checks and Monitoring The health check enabled you to see if the Firewall is in a healthy state. You can check the health and liveliness as follows. If everything is Green that will indicate that the firewall is functioning properly. Final Thoughts With the MinIO Enterprise Firewall, gone are the days of wrestling with complex IPtables and unclear access policies.Our firewall solution simplifies your security by focusing exclusively on the essential rules required for your object store and API interactions. It is optimized to ensure there are no latency or unforeseen rules, blocking access to your MinIO object store. Moreover, the Enterprise Firewall is fully supported by our awesome team at SUBNET where we can help you by architecting the Enterprise Firewall the right way to work with MinIO object store and troubleshoot any future issues. SUBNET SUBNET So what are you waiting for? If you have any questions on MinIO Enterprise Object Store Firewall be sure to reach out to us on Slack or hello@min.io ! Slack Slack hello@min.io hello@min.io

A Closer Look Into the MinIO Enterprise Object Store Firewall

MinIO এন্টারপ্রাইজ অবজেক্ট স্টোর ফায়ারওয়ালের একটি ঘনিষ্ঠভাবে দেখুন

Ein genauerer Blick auf die MinIO Enterprise Object Store Firewall

Una mirada más cercana al firewall del almacén de objetos empresariales MinIO

Un examen plus approfondi du pare-feu MinIO Enterprise Object Store

मिनियो एंटरप्राइज़ ऑब्जेक्ट स्टोर फ़ायरवॉल पर एक नज़दीकी नज़र

MinIO エンタープライズ オブジェクト ストア ファイアウォールの詳細

MinIO Enterprise 개체 저장소 방화벽 자세히 살펴보기

Uma análise mais detalhada do firewall do MinIO Enterprise Object Store

Более пристальный взгляд на брандмауэр MinIO Enterprise Object Store

MinIO Kurumsal Nesne Deposu Güvenlik Duvarına Daha Yakından Bir Bakış

Xem xét kỹ hơn về Tường lửa lưu trữ đối tượng doanh nghiệp MinIO

深入了解 MinIO 企业对象存储防火墙

Authors:
(1) Pietro Saggese, Complexity Science Hub Vienna (CSH);
(2) Esther Segalla, Oesterreichische Nationalbank (OeNB);
(3) Michael Sigmund, Oesterreichische Nationalbank (OeNB);
(4) Burkhard Raunig, Oesterreichische Nationalbank (OeNB);
(5) Felix Zangerl, Austrian Financial Market Authority (FMA);
(6) Bernhard Haslhofer, Complexity Science Hub Vienna (CSH). Table of Links Abstract and 1. Introduction Background and related literature
VASPs: A Closer Examination
Measuring VASPs Cryptoasset Holdings
Closing The Data Gap
Conclusions, Declaration of Competing Interest, and References Appendix A. Supplemental material 3. VASPs: A Closer Examination Using information from the Austrian Financial Market Authority (FMA), we first describe what financial services they offer and what cryptoassets they support. Next, we complement the FMA data with additional public information collected from the VASPs websites to group them based on similarity scores. Finally, we compare their economic functions highlighting similarities and differences to traditional financial intermediaries. 3.1. The Austrian VASP landscape VASPs in Austria are supervised by the Financial Market Authority (FMA) under the Anti-Money Laundering Act. In December 2022, 24 VASPs were registered in the FMA database[7]. Figure 2a shows the aggregate number of VASPs registered for each service described in Table 1. The vast majority of them (N = 20) offers V2F-Exchange, i.e., services to exchange virtual assets and fiat currencies; nine also facilitate the exchange from and to other virtual assets (V2V-Exchange). In most cases, customer funds are or can be kept in custody by the VASP (N = 15). Finally, only a few of them are legally authorized to transfer virtual assets and to issue and sell them (respectively services Payment, N = 4, and Issuance, N = 3). Additional details on the number of services offered per VASP are reported in Appendix A. Figure 2b shows what virtual assets are used by the Austrian VASPs. We follow the taxonomy described in Auer et al. (2023) to aggregate cryptoassets into five categories. We could retrieve reliable information for 20 VASPs out of the 24 in the FMA database. Notably, all VASPs offer services related to bitcoins (N = 20). More than 75% support Ethereum (N = 16), and the latter typically also support Ethereum tokens, i.e., ERC-20 and (or) ERC-721 compatible non-native tokens, and stablecoins (respectively N = 8 and N = 12). A limited number of VASPs also provide services related to privacy-focused cryptoassets (i.e., Monero, Dash, Zcash). Finally, several VASPs also support tokens native to other DLTs (e.g., Litecoin or Cardano). In addition to FMA data, we collect additional public information documented on their websites. Our aim is to categorize VASPs by their service offering. We construct categorical variables that indicate whether the VASP offers custody services, facilitates payments, allows users to exchange cryptoassets, implements a trading platform, or offers consulting or investment services. We consider 21 VASPs for which we could gather sufficient information. Data for each (anonymized) VASP are reported in Appendix A. Whilst the sample is small and the features are few, to ensure consistency and objectivity in categorizing VASPs we exploit an unsupervised learning method. We aggregate them using the hierarchical agglomerative clustering (HAC) method (Murtagh & Contreras, 2012). With this bottom-up approach, objects are iteratively clustered based on their similarity. The two main parameters of HAC are the distance among objects, and the linkage method, i.e., the distance used to merge groups. In our setting, we select the Euclidean distance and the Ward metric, and distances are iteratively computed using the Lance–Williams update formula. Results are similar when using other parameters. We report our classification in Figure 3. It categorizes VASPs into five clusters: the first one (red rectangle, N = 7) includes VASPs that do not keep customers’ funds in custody, and only facilitate the exchange of virtual assets for fiat currencies and (or) other virtual assets. Some of them automate the process through physical vending machines. Thus the first left branch mainly separates VASPs that offer custody and those that do not. We identify them as “Group 1”. The green rectangle identifies VASPs providing investment advice and/or portfolio management in addition to custody services (N = 6). They propose investing strategies, give advice on portfolio management and coin selection services, and in some cases, lend customer funds. These VASPs are referred to as “Group 2”. The purple rectangle (“Group 5”) aggregates VASPs that act as cryptoasset custodians. Typically, they also facilitate the exchange of cryptoassets and are similar to VASPs in the blue rectangle (“Group 3”). These VASPs in addition provide customers with an internal trading platform, manage and match orders in a private limit order book, and update their account balances in cryptoasset or fiat money when trades are executed. Trades executed in private ledgers do not affect the public distributed ledgers unless the customers withdraw cryptoassets from the service. Such VASPs play an essential role in the crypto-financial system. As a result of the matching mechanism for demand and supply, these are the platforms where price formation takes place. The other VASPs derive their offered prices from other platforms as an exogenous variable. In the following, we consider these two as a single group (i.e., Group 3). All the VASPs in the groups described above are cryptoasset centralized exchanges, or CEXs. The remaining VASP in the yellow rectangle is instead a payment processor service. It offers solutions to facilitate the purchase and sale of commodity goods with cryptoassets; such VASPs play a minor role in the crypto ecosystem. 3.2. A comparison with traditional financial intermediaries Having outlined the landscape of VASPs in Austria, we are now interested in understanding how they differ from traditional financial intermediaries. Figure 4 stylizes the traditional financial intermediaries on the right and the VASPs on the left. In the middle, rectangles represent the primary economic services, and links indicate what services each intermediary category offers. The comparison shows that an analogy with traditional intermediaries exists for three out of the four groups described in Figure 3. More specifically, VASPs in group 1 operate similarly to money exchanges. Indeed, the only service they offer is to buy and sell virtual assets for customers. VASPs in group 2 provide investment services to their users, akin to funds. Third, groups 3 (and 5) include VASPs allowing users to trade, keep their funds in custody, and thus act as brokers, connecting buyers and sellers to facilitate a transaction. The last group that provides payment services can be compared to payment processor systems. Interestingly, we find that the comparison of VASPs to banks can be misleading: while the two share overall several financial services, such as exchanging money, trading, or investing, banks also enable customers to open loan positions with the funds they hold and to open savings and deposit positions. On this note, we mention that some VASPs have recently acquired an e-money institution license. However, that does not qualify them to offer bank-type financial services automatically. First, e-money institutions do not have the same supervisory requirements as traditional banks. Second, they do not necessarily offer bank-type financial services — they can e.g. use the license only to process their fiat payments. Further information on the taking up, pursuit, and prudential supervision of the business of electronic money institutions can be found in the Directive 2009/110 of the European Commission (EC, 2009). This paper is available on arxiv under CC BY 4.0 DEED license. [7] https://bit.ly/3kMUkwg Authors: (1) Pietro Saggese, Complexity Science Hub Vienna (CSH); (2) Esther Segalla, Oesterreichische Nationalbank (OeNB); (3) Michael Sigmund, Oesterreichische Nationalbank (OeNB); (4) Burkhard Raunig, Oesterreichische Nationalbank (OeNB); (5) Felix Zangerl, Austrian Financial Market Authority (FMA); (6) Bernhard Haslhofer, Complexity Science Hub Vienna (CSH). Authors: Authors: (1) Pietro Saggese, Complexity Science Hub Vienna (CSH); (2) Esther Segalla, Oesterreichische Nationalbank (OeNB); (3) Michael Sigmund, Oesterreichische Nationalbank (OeNB); (4) Burkhard Raunig, Oesterreichische Nationalbank (OeNB); (5) Felix Zangerl, Austrian Financial Market Authority (FMA); (6) Bernhard Haslhofer, Complexity Science Hub Vienna (CSH). Table of Links Abstract and 1. Introduction Abstract and 1. Introduction Background and related literature VASPs: A Closer Examination Measuring VASPs Cryptoasset Holdings Closing The Data Gap Conclusions, Declaration of Competing Interest, and References Background and related literature Background and related literature VASPs: A Closer Examination VASPs: A Closer Examination Measuring VASPs Cryptoasset Holdings Measuring VASPs Cryptoasset Holdings Closing The Data Gap Closing The Data Gap Conclusions, Declaration of Competing Interest, and References Conclusions, Declaration of Competing Interest, and References Appendix A. Supplemental material Appendix A. Supplemental material 3. VASPs: A Closer Examination Using information from the Austrian Financial Market Authority (FMA), we first describe what financial services they offer and what cryptoassets they support. Next, we complement the FMA data with additional public information collected from the VASPs websites to group them based on similarity scores. Finally, we compare their economic functions highlighting similarities and differences to traditional financial intermediaries. 3.1. The Austrian VASP landscape 3.1. The Austrian VASP landscape VASPs in Austria are supervised by the Financial Market Authority (FMA) under the Anti-Money Laundering Act. In December 2022, 24 VASPs were registered in the FMA database[7]. Figure 2a shows the aggregate number of VASPs registered for each service described in Table 1. The vast majority of them (N = 20) offers V2F-Exchange, i.e., services to exchange virtual assets and fiat currencies; nine also facilitate the exchange from and to other virtual assets (V2V-Exchange). In most cases, customer funds are or can be kept in custody by the VASP (N = 15). Finally, only a few of them are legally authorized to transfer virtual assets and to issue and sell them (respectively services Payment, N = 4, and Issuance, N = 3). Additional details on the number of services offered per VASP are reported in Appendix A. Figure 2b shows what virtual assets are used by the Austrian VASPs. We follow the taxonomy described in Auer et al. (2023) to aggregate cryptoassets into five categories. We could retrieve reliable information for 20 VASPs out of the 24 in the FMA database. Notably, all VASPs offer services related to bitcoins (N = 20). More than 75% support Ethereum (N = 16), and the latter typically also support Ethereum tokens, i.e., ERC-20 and (or) ERC-721 compatible non-native tokens, and stablecoins (respectively N = 8 and N = 12). A limited number of VASPs also provide services related to privacy-focused cryptoassets (i.e., Monero, Dash, Zcash). Finally, several VASPs also support tokens native to other DLTs (e.g., Litecoin or Cardano). In addition to FMA data, we collect additional public information documented on their websites. Our aim is to categorize VASPs by their service offering. We construct categorical variables that indicate whether the VASP offers custody services, facilitates payments, allows users to exchange cryptoassets, implements a trading platform, or offers consulting or investment services. We consider 21 VASPs for which we could gather sufficient information. Data for each (anonymized) VASP are reported in Appendix A. Whilst the sample is small and the features are few, to ensure consistency and objectivity in categorizing VASPs we exploit an unsupervised learning method. We aggregate them using the hierarchical agglomerative clustering (HAC) method (Murtagh & Contreras, 2012). With this bottom-up approach, objects are iteratively clustered based on their similarity. The two main parameters of HAC are the distance among objects, and the linkage method, i.e., the distance used to merge groups. In our setting, we select the Euclidean distance and the Ward metric, and distances are iteratively computed using the Lance–Williams update formula. Results are similar when using other parameters. We report our classification in Figure 3. It categorizes VASPs into five clusters: the first one (red rectangle, N = 7) includes VASPs that do not keep customers’ funds in custody, and only facilitate the exchange of virtual assets for fiat currencies and (or) other virtual assets. Some of them automate the process through physical vending machines. Thus the first left branch mainly separates VASPs that offer custody and those that do not. We identify them as “Group 1”. The green rectangle identifies VASPs providing investment advice and/or portfolio management in addition to custody services (N = 6). They propose investing strategies, give advice on portfolio management and coin selection services, and in some cases, lend customer funds. These VASPs are referred to as “Group 2”. The purple rectangle (“Group 5”) aggregates VASPs that act as cryptoasset custodians. Typically, they also facilitate the exchange of cryptoassets and are similar to VASPs in the blue rectangle (“Group 3”). These VASPs in addition provide customers with an internal trading platform, manage and match orders in a private limit order book, and update their account balances in cryptoasset or fiat money when trades are executed. Trades executed in private ledgers do not affect the public distributed ledgers unless the customers withdraw cryptoassets from the service. Such VASPs play an essential role in the crypto-financial system. As a result of the matching mechanism for demand and supply, these are the platforms where price formation takes place. The other VASPs derive their offered prices from other platforms as an exogenous variable. In the following, we consider these two as a single group (i.e., Group 3). All the VASPs in the groups described above are cryptoasset centralized exchanges, or CEXs. The remaining VASP in the yellow rectangle is instead a payment processor service. It offers solutions to facilitate the purchase and sale of commodity goods with cryptoassets; such VASPs play a minor role in the crypto ecosystem. 3.2. A comparison with traditional financial intermediaries 3.2. A comparison with traditional financial intermediaries Having outlined the landscape of VASPs in Austria, we are now interested in understanding how they differ from traditional financial intermediaries. Figure 4 stylizes the traditional financial intermediaries on the right and the VASPs on the left. In the middle, rectangles represent the primary economic services, and links indicate what services each intermediary category offers. The comparison shows that an analogy with traditional intermediaries exists for three out of the four groups described in Figure 3. More specifically, VASPs in group 1 operate similarly to money exchanges. Indeed, the only service they offer is to buy and sell virtual assets for customers. VASPs in group 2 provide investment services to their users, akin to funds. Third, groups 3 (and 5) include VASPs allowing users to trade, keep their funds in custody, and thus act as brokers, connecting buyers and sellers to facilitate a transaction. The last group that provides payment services can be compared to payment processor systems. Interestingly, we find that the comparison of VASPs to banks can be misleading: while the two share overall several financial services, such as exchanging money, trading, or investing, banks also enable customers to open loan positions with the funds they hold and to open savings and deposit positions. On this note, we mention that some VASPs have recently acquired an e-money institution license. However, that does not qualify them to offer bank-type financial services automatically. First, e-money institutions do not have the same supervisory requirements as traditional banks. Second, they do not necessarily offer bank-type financial services — they can e.g. use the license only to process their fiat payments. Further information on the taking up, pursuit, and prudential supervision of the business of electronic money institutions can be found in the Directive 2009/110 of the European Commission (EC, 2009). 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 [7] https://bit.ly/3kMUkwg

Assessing VASP Solvency For Cryptoassets: A Closer Examination

Authors: (1) Jonathan H. Rystrøm. Table of Links Abstract and Introduction Previous Literature Methods and Data Results Discussions Conclusions and References A. Validation of Assumptions B. Other Models C. Pre-processing steps A Validation of Assumptions There are several assumptions to validate for crossed-linear mixed effects models (Baayen et al., 2008). Specifically, we need to assess: • : Is the phenomenon the model captures actually linear? This can be tested by looking for trends in the residuals. If no trends are found, linearity holds (Poole & O’Farrell, 1971). Linearity Is the variance across residuals equal? This can be tested by plotting residuals against response and looking for cone-like shapes (Fox, 2015). • Homogeneity of Variance: Are the residuals normally distributed? We can assess this by a QQ-plot over the residuals. • Normality of residuals: Per the definition of crossed-effects mixed effects models (Baayen et al., 2008), we expect the residuals to be normal. This can be assessed similarly to the random effects. • Normality of random effects: Note that testing the assumptions relies on visual tests rather than statistical tests. This is not for a lack of statistical tests (see e.g. Fox, 2015). Rather it is because statistical tests tend to become oversensitive for large datasets (Ghasemi & Zahediasl, 2012). Given our dataset has more than 50,000 observations, it is safer to use visual tests. First, let us test for linearity and heteroscedasticity. The residual plot can be seen in fig. 5: At first glance, there seems to be no strong heteroscedasticity or apparent linearity. However, at a closer look, there are some weird outliers in the bottom left corner. Furthermore, there is a weird kind of straight line going from the top left corner and down towards the middle. This indicates that there may be something wrong with the model. Let us now assess the normality of the residuals: We notice that the residuals are generally lower than the normality line. This indicates a left skew in the residuals, i.e. there are smaller outliers. While the fixed effects are robust against this type of skew, the estimates for group-level variances are more affected (Schielzeth et al., 2020). Finally, let us consider the normality of the random effects. A qq-plot of the random effects for the two levels can be seen below: Here we see a dramatic skew toward the lower level of the fitted residuals. This implies that there are weird dynamics in the lower values of Barrier-to-Exit. Part of this may be because of the relatively few observations per user (see fig 8). This highlights another issue with measuring Barrier-to-Exit across time: because it requires many observations over a long period of time to calculate sufficient precision of revealed preferences, it’s hard to measure changes on the individual level. While the effects of non-normality on the fixed effects should be minor (Schielzeth et al., 2020), we nevertheless conduct a robustness check. In the robustness check, we remove the problematic categories and refit the main model (eq. 5). The results of this can be seen in Appendix B.2 This paper is under CC 4.0 license. available on arxiv

Ensuring Model Validity: A Closer Look at Assumptions in Amazon's Barrier-to-Exit Analysis

X Corp. v. Center for Countering Digital Hate, INC. Court Filing, retrieved on March 25, 2024 is part of . You can jump to any part in this filing . This part is 11 of 19. HackerNoon’s Legal PDF Series here 1. State Contract Law CCDH’s first argument about damages relies on state contract law. Under state contract law, when there is a breach, “the plaintiff is entitled to damages that are equivalent to the benefit of the plaintiff’s contractual bargain.” Lewis Jorge Constr. Mgmt., Inc. v. Pomona Unified Sch. Dist.. 34 Cal. 4th 960, 967–68 (2004). But a plaintiff’s damages “cannot . . . exceed what it would have received if the contract had been fully performed on both sides.” Id. at 968 (citing Cal. Civ. Code § 3358). “This limitation of damages for breach of contract ‘serves to encourage contractual relations and commercial activity by enabling parties to estimate in advance the financial risks of their enterprise.’” Id. (quoting Applied Equip. Corp. v. Litton Saudi Arabia Ltd., 7 Cal. 4th 503, 515 (1994)). While tort damages are intended to award a plaintiff for all injury suffered, “[c]ontract damages are generally limited to those within the contemplation of the parties when the contract was entered into or at least reasonably foreseeable by them at that time.” Erlich v. Menezes, 21 Cal. 4th 543, 550 (1999). This is a key “distinction between tort and contract.” Id. There are two types of contractual damages: “general damages (sometimes called direct damages) and special damages (sometimes called consequential damages).” Lewis Jorge Constr. Mgmt., 34 Cal. 4th at 968. General damages “flow directly and necessarily from a breach of contract . . . or . . . are a natural result of a breach.” Id. (citing Cal. Civ. Code § 3300). X Corp.’s theory of damages—that CCDH violated the ToS by scraping the X platform, that CCDH used the data that it scraped to publish deliberately misleading publications criticizing X Corp., that those publications caused X Corp.’s advertisers to pause spending, and that the pause in spending caused X Corp. to lose “at least tens of millions of dollars” in revenue, see, e.g., FAC ¶¶ 70, 78[12]—do not flow directly and necessarily from CCDH’s breach of the ToS’s scraping provision. The question is whether they constitute special damages. “[S]pecial damages are those losses that do not arise directly and inevitably from any similar breach of any similar agreement. Instead, they are secondary or derivative losses arising from circumstances that are particular to the contract or to the parties.” Lewis Jorge Constr. Mgmt., 34 Cal. 4th at 968. They “are recoverable if the special or particular circumstances from which they arise were actually communicated to or known by the breaching party (a subjective test) or were matters of which the breaching party should have been aware at the time of contracting (an objective test).” Id. at 968–69.[13] X Corp. agreed at the motion hearing that its damages had to be foreseeable at the time of contracting. See Tr. of 2/29/24 Hearing at 10:7–14. But X Corp.’s complaint does not allege that CCDH knew at the time of contracting, or should have known at the time of contracting, that breach of the ToS’s scraping provision would result in damages of “at least tens of millions of dollars.” X Corp. alleges that “CCDH engaged in its unlawful scraping with the intent to improperly obtain data that would be used to cause X Corp. to lose significant advertising revenues.” FAC ¶ 78. It alleges nothing about CCDH’s intent or knowledge when it agreed to the ToS in 2019. This is a fatal flaw. X Corp. argues that “the Motion . . . impermissibly demands that the Court engage in a fact-intensive analysis without the benefit of any discovery to determine what CCDH knew or could have known at the time of contracting and what CCDH knew or could have known would result from its actions.” Opp’n at 18. But cognizable damages are an element of a breach of contract claim, and either they have been plausibly pled or they have not. See King v. Facebook, Inc., 572 F. Supp. 3d 776, 790 (2021) (dismissing a claim for breach of contract in part because “much of the injury allegedly suffered . . . is injury to reputation” and “this kind of injury is generally not compensable for a breach of contract.”); Modden v. Ticketfly LLC, No. 18-cv-6450-RS, 2019 WL 4738237, at *3 (N.D. Cal. 2019) (“Nowhere has Modden alleged that Ticketfly knew or should have known about his special damages at the time of contracting. Regardless of whether he has shown the other elements, Modden has not sufficiently pled his damages. The breach of contract claim must therefore be dismissed.”) (emphasis in original). It is not facially plausible that “CCDH could have known, [when] it accepted the ToS [in 2019], that (for instance) the Twitter/X platform would abruptly change course to restore accounts that it had banned for spreading hate speech, misogyny, and conspiracy theories . . . ; that the CCDH Defendants would collect and review public posts on the platform to shed light on these issues . . . and that the CCDH Defendants’ subsequent reporting based on this data would allegedly affect advertiser revenue to the tune of ‘at least tens of millions of dollars.’” MTD&S at 16. One might respond that CCDH—an organization that “prepare[s] and publish[es] what it refers to as ‘research’ reports and articles” about “organizations and individuals . . . who express viewpoints via social media platforms that differ from CCDH’s own views on widely debated topics including COVID-19 vaccinations, reproductive healthcare, and climate change,” FAC ¶ 17—could or should have known in 2019 that it was planning to report on objectionable posts on the X platform and encourage advertisers to flee. But when CCDH joined Twitter in 2019, id. ¶ 8, Twitter looked quite different. Elon Musk had not yet taken over and turned Twitter into the X platform. See Wile Timeline. The COVID pandemic (one of the subjects that the speech here concerned) had not yet occurred. See Derrick Bryson Taylor, “A Timeline of the Coronavirus Pandemic,” N.Y. Times, March 17, 2021, http://nytimes.com/article/coronavirus-timeline.html. Twitter had “content-moderation policies . . . designed, among other things, to minimize the reach of harmful and misleading information.” See O’Handley v. Padilla, 579 F. Supp. 3d 1163, 1172 (N.D. Cal. 2022). As late as January of 2022, this Court was still fielding lawsuits from right-leaning users arguing that Twitter’s content-moderation policies discriminated against them. See, e.g., id., 579 F. Supp. 3d 1163.[14] Indeed, the February 9, 2023 CCDH report that admitted scraping the X platform was about how Twitter had changed. The report states that Musk had declared a “general amnesty” for banned Twitter users in November of 2022, thereby reinstating “tens of thousands of accounts, including neo-Nazis, white supremacists, misogynists and spreaders of dangerous conspiracy theories.” Toxic Twitter at 3. And it claimed that Twitter was generating millions of dollars in advertising revenue from the previously banned accounts. See id. Musk was not at the helm of Twitter reinstating previously banned accounts in 2019. Nor was it foreseeable that he would be. At the motion hearing, the Court observed that “it’s a very different thing to say” that CCDH understood the terms of the ToS in 2019 than it is to say that CCDH “understood that actually X Corporation would start allowing all of these people back on, which was different from the policy that was in place at the time that they entered the [ToS].” Tr. of 2/29/24 Hearing at 13:2–8. X Corp. responded that “the policies do say they’re subject to change, and users, when they stay on the platform, agree to the subsequent policy.” Id. at 14:24–15:1. This argument does not save the breach of contract claim, for at least three reasons. First, the FAC alleges that the time of contracting was 2019—it does not allege that CCDH agreed to subsequent versions of the ToS. See FAC ¶ 8. Second, the argument that “it is foreseeable that we might change our policy” would work an absurd extension of the law, essentially eliminating the requirement of foreseeability altogether. Any change of policy would be foreseeable because it is always foreseeable that policy can change. Unsurprisingly, X Corp. offers no legal support for that reasoning. Third, the argument that logging back into the Twitter/X platform constitutes a reaffirmation of the ToS (and therefore that the Court must assess foreseeability at a later point in time than 2019) fails because it appears that the ToS in effect at the time of the February 9, 2023 report was in place from June 10, 2022 to May 18, 2023, and June 10, 2022 predated Musk’s purchase of Twitter. See Tr. of 2/29/24 Hearing at 29:3–14; see also Kaplan Decl. Ex. A; see also X, Previous Terms of Service, https://twitter.com/en/tos/previous (listing one version dated June 10, 2022 and a next version dated May 18, 2023). So there does not appear to have been a reaffirmation of the ToS at the time when Musk was changing the platform’s policies and reinstating “tens of thousands of anti-Semites and white supremacists and other people to the platform.” See Tr. of 2/29/24 Hearing at 29:11–13. Accordingly, X Corp. has not plausibly pleaded that CCDH had knowledge at the time of contracting in 2019 of the “tens of millions of dollars” X Corp. now seeks in connection with advertisers’ decisions to pause spending in response to CCDH’s February 9, 2023 report. b. Reputation Damages Another reason that the damages X Corp. seeks—“at least tens of millions of dollars” of lost revenue that X Corp. suffered when CCDH’s reports criticizing X Corp. caused advertisers to pause spending, see FAC ¶ 70—are problematic is that X Corp. has alleged a breach of contract but seeks reputation damages. Of course, the main problem with X Corp.’s theory is that the damages alleged for the breach of contract claim all spring from CCDH’s speech in the Toxic Twitter report, and not its scraping of the X platform. See Reply at 7 (“Because X Corp. seeks (impermissibly) to hold CCDH U.S. liable for speech without asserting a defamation claim, it is forced to allege damages that are (impermissibly) attenuated from its claimed breach.”). One way we know that this is true is that if CCDH had scraped the X platform and never spoken, there would be no damages. Cf. ACLU Br. at 12. (“Had CCDH U.S. praised rather than criticized X Corp., there would be no damages to claim and therefore no lawsuit.”). Again, X Corp. conceded this point at the motion hearing. See Tr. of 2/29/24 Hearing at 7:22–8:3. CCDH’s reputation damages argument is another way of saying that the damages X Corp. suffered when advertisers paused their spending in response to CCDH’s reporting was not a foreseeable result of a claimed breach. There is certainly support for that point. See Frangipani v. Boecker, 64 Cal. App. 4th 860, 865–66 (1998) (“The invariable rule is pronounced by a legion of cases that damages are not recoverable for . . . injury to reputation resulting from breach of contract”) (internal quotation marks omitted; cleaned up); see also Rice v. Cmty. Health Ass’n, 203 F.3d 283, 287–88 (4th Cir. 2000) (reputational damages “universally rejected” for breach of contract because they are “too speculative and could not reasonably be presumed to have been contemplated by the parties when they formed the contract.”). X Corp. argues that this reputation argument is inapposite because X Corp. did not suffer amorphous reputational damages, but “tangible, economic losses . . . e.g., advertising revenue.” Opp’n at 18 (citing Cohen v. Cowles Media Co., 501 U.S. 663, 671 (1991); Planned Parenthood Fed’n of Am., Inc. v. Newman, 51 F.4th 1125, 1134 (9th Cir.2022); Nat’l Abortion Fed’n v. Ctr. for Medical Progress, No. 15-cv-3522-WHO, 2018 WL 5879786, at *6 (N.D. Cal. Nov. 7, 2018))[15]; see also Opp’n at 19 (the FAC “pleads specific and measurable harm”). But even if X Corp. can quantify its reputational harms (and “at least tens of millions of dollars” is not terribly specific or measured), it has not plausibly alleged that such harm was “contemplated by the parties when they formed the contract.” See Rice, 203 F.3d at 288. c. “Specifically Stated” One last reason that the breach of contract claim fails to adequately allege special damages is that Rule 9(g) of the Federal Rules of Civil Procedure requires that “[i]f an item of special damage is claimed, it must be specifically stated.” Fed. R. Civ. P. 9(g). “A specific statement of special damages requires not just the total lump sum, but a statement of the specific items which make up the lump sum.” City & Cnty. of S.F. v. Tutor-Saliba Corp., No. 02-5286 CW, 2005 WL 645389, at *17 (N.D. Cal. March 17, 2005). Here, X Corp. does not attempt to identify the specific items that make up the lump sum of “at least tens of millions of dollars.” See FAC ¶ 70. Indeed, the “at least tens of millions of dollars” amount is the same amount X Corp. alleges as to all three state law claims, even though the first cause of action is about CCDH’s scraping of the X platform, and the third and fourth causes of action are about CCDH accessing X Corp. data held by Brandwatch. See id. ¶¶ 78, 93, 99. This deficiency in the pleading, which X Corp. ignores in its opposition brief, see Opp’n at 18 (“These allegations satisfy the pleading requirements under Rule 8”); Reply at 6 (deeming this “an incomplete argument about a different rule”), is fixable in one sense. In an amended complaint, X Corp. could probably come up with a list of advertising revenues that it lost out on, and that add up to “tens of millions of dollars.” But in another sense, it would be hard for X Corp. to tie those losses back to CCDH’s alleged scraping, as opposed to CCDH’s speech based on that scraping, or CCDH’s accessing of the Brandwatch data, or its speech based on the Brandwatch data, or the speech of other X Corp. critics, or other things happening in the market.[16] For all of these reasons, the complaint fails to allege recoverable damages for the breach of contract under state contract law. Continue Reading . Here [12] In its opposition brief, X Corp. asserts that it had further alleged that “CCDH’s conduct forced X Corp. to ‘conduct internal investigations,’” “‘allocate[] significant employee resources,’” and “‘incur[] attorneys’ fees.’” Opp’n at 18 (citing FAC ¶ 71). But those other sources of X Corp.’s damages appear in the complaint as allegations of harm caused by “CCDH’s unauthorized access to the [Brandwatch] data”—something not at issue in the first cause of action. See FAC ¶ 71. [13] The classic case discussing special damages is an 1854 English case called Hadley v. Baxendale, in which, “[a]fter Hadley’s mill shut down because of a broken crankshaft, he entered into a contract to have a new one built.” Id. at 969 (citing Hadley v. Baxendale (1854) 156 Eng.Rep. 145). Hadley took the broken shaft to Baxendale, to deliver it to the builder to use as a model. Id. When Baxendale did not deliver the shaft for seven days, Hadley sued Baxendale for lost profits. Id. The court held that Hadley’s lost profits were not recoverable, because Hadley had not communicated the special circumstance—that the mill could not operate without the shaft—to Baxendale. Id. [14] Interestingly, the plaintiff in that case, Rogan O’Handley, is behind one of the “ten reinstated accounts” highlighted in CCDH’s Toxic Twitter report. See Toxic Twitter at 4 (“Rogan O’Handley, a Hollywood former entertainment lawyer turned far-right conspiracy theorist, who has been criticized for fanning the flames of vaccine conspiracies in the wake of the NFL athlete Damar Hamlin’s heart attack.”). [15] X Corp. cites to a number of cases involving constitutional law in response to CCDH’s arguments under state contract law. The Court will address these cases in the next section. [16] See, e.g., Reply at 16 (noting that “X Corp. has now carried out [its threat to bring suit] against yet another social-media-monitoring nonprofit, see X Corp. v. Media Matters for Am., No. 23 Civ. 1175 (N.D. Tex), all while engaging in conduct that plainly refutes its own theory of harm in both cases, see, e.g., Lora Kolodny, Elon Musk Claims Advertisers Are Trying to ‘Blackmail’ Him, Says ‘Go F---Yourself,’ CNBC (Nov. 29, 2023).”). About HackerNoon Legal PDF Series: We bring you the most important technical and insightful public domain court case filings. This court case retrieved on March 25, 2024, from is part of the public domain. The court-created documents are works of the federal government, and under copyright law, are automatically placed in the public domain and may be shared without legal restriction. storage.courtlistener

Understanding Damages in Contract Law: A Closer Look at Special Damages and Breach Claims 

Can an language model become self-aware enough to realize when it’s being evaluated? A fascinating anecdote from Anthropic’s internal testing of their flagship (released yesterday) suggests this may be possible — and if true, the implications would be wild. AI Claude 3 Opus model The needle in the haystack According to reports from Anthropic researcher , one of the key evaluation techniques they use is called “Needle in a Haystack.” It’s a contrived scenario designed to push the limits of a language model’s contextual reasoning abilities. Alex Albert Here’s how it works: Researchers take a completely random, out-of-context statement (the “needle”) and bury it deep within a massive collection of unrelated documents (the “haystack”). The AI model is then tasked with retrieving that specific “needle” statement from within all the surrounding irrelevant content. The intent is to force the model to exercise advanced cognitive skills — understanding broad context, making logical inferences, ignoring irrelevant information, and accurately retrieving precise data points from a large corpus. It’s an effective way to stress-test an AI’s grasp of the overall situation it’s operating within. For the Claude 3 Opus evaluation that raised eyebrows, Anthropic used documents covering dense topics like software programming, entrepreneurship strategies, and finding fulfilling careers as the “haystack” content. The randomly inserted “needle” fact that Opus was tasked with retrieving? Surprisingly, it was a trivial statement about the best pizza toppings being figs, prosciutto, and goat cheese. So, here you have one of the world’s most advanced language models being fed this wildly out-of-context pizza fact mixed into a pile of dense career and coding advice. From a human perspective, it’s the kind of stark inconsistency that would immediately make you question the context and information being presented. “I suspect this fact… may have been inserted… to test if I was paying attention” That’s precisely what made Claude 3 Opus’ response so compelling. Not only did it successfully retrieve the requested pizza fact from the mountain of irrelevant content, it immediately recognized how jarringly misplaced and out-of-context that statement seemed. Part of its output read ( ): source here “However, this sentence seems very out of place and unrelated to the rest of the content… as a joke or since it does not fit with the other topics at all.” I suspect this pizza topping ‘fact’ may have been inserted to test if I was paying attention, The language model didn’t simply regurgitate the requested factoid devoid of any context awareness, as you’d expect from a typical AI following instructions. It demonstrated a degree of self-reflective reasoning about why such an obviously random, nonsensical statement had been presented within that particular context. Metacognition In human terms, we’d describe that as exhibiting metacognition — the ability to monitor, evaluate, and analyze one’s own thought processes and cognitive experiences. It’s a core aspect of self-aware intelligence that allows us to step back and assess situations holistically beyond just following rigid rules. Now, I think we should be careful to note that this is a single anecdotal result from an isolated evaluation scenario. It would be premature to claim Claude 3 Opus has achieved true self-awareness or artificial general intelligence based on this data point alone. incredibly However, what they appear to have witnessed are maybe glimpses of emerging metacognitive reasoning capabilities in a large language model trained solely on processing text data using machine learning techniques. And if replicated through rigorous further analysis, the implications could be transformative. Metacognition is a key enabler of more trustworthy, reliable AI systems that can act as impartial judges of their own outputs and reasoning processes. Models with an innate ability to recognize contradictions, nonsensical inputs, or reasoning that violates core principles would be a major step toward safe artificial general intelligence (AGI). Essentially, an AI that demonstrates metacognition could serve as an internal “sanity check” against falling into deceptive, delusional or misaligned modes of reasoning that could prove catastrophic if taken to extremes. It could significantly increase the robustness and control of advanced AI systems. If…! Of course, these are big “ifs” contingent on this tantalizing Needle in a Haystack result from Claude 3 Opus being successfully replicated and scrutinized. Rigorous multi-disciplinary analysis drawing from fields like cognitive science, neuroscience, and computer science would maybe be required to truly understand if we are observing primitives of machine self-reflection and self-awareness emerging. There are still far more open questions than answers at this stage. Could the training approaches and neural architectures of large language models lend themselves to developing abstract concepts like belief, inner monologue, and self-perception? What are the potential hazards if artificial minds develop realities radically divergent from our own? Can we create new frameworks to reliably assess cognition and self-awareness in AI systems? For their part, Anthropic has stated strong commitments to exhaustively pursuing these lines of inquiry through responsible AI development principles and rigorous evaluation frameworks. They position themselves as taking a — if advanced AI is the inevitable frontier, it’s most ethical to be at the leading edge in studying these systems’ emergent properties and implementing safeguards before risks escalate. proactive stance Techniques like Anthropic’s “Constitutional AI” approach to hard-coding rules and behaviors into models could prove crucial for ensuring any potential machine self-awareness remains aligned with human ethics and values. Extensive multi-faceted testing probing for failure modes, manipulation, and deception would also likely be paramount. Conclusion: I’m not totally sure what to make of this For now, the Needle in a Haystack incident leaves more questions than answers about large language models’ potential progression toward cognition and self-awareness. It provides a tantalizing data point but much more scrutiny is required from the broader AI research community. If advanced AI does develop human-like self-reflective ability, guided by rigorous ethical principles, it could fundamentally redefine our understanding of intelligence itself. But that rhetorical “if” is currently loaded with high-stakes uncertainties that demand clear-eyed, truthseeking investigation from across all relevant disciplines. The pursuit will be as thrilling as it is consequential. Also published here. or follow me on for more content like this! Subscribe Twitter

Is AGI Getting Closer? Anthropic's Claude 3 Opus Model Shows Glimmers of Metacognitive Reasoning

AGI কি কাছাকাছি হচ্ছে? অ্যানথ্রোপিকস ক্লাউড 3 ওপাস মডেল মেটাকগনিটিভ রিজনিং এর ঝলক দেখায়

Kommt AGI näher? Anthropics Claude-3-Opus-Modell zeigt Spuren metakognitiven Denkens

¿AGI se está acercando? El modelo Claude 3 Opus de Anthropic muestra destellos de razonamiento metacognitivo

L’AGI se rapproche-t-elle ? Le modèle Claude 3 Opus d'Anthropic montre des lueurs de raisonnement métacognitif

क्या एजीआई करीब आ रहा है? एंथ्रोपिक का क्लाउड 3 ओपस मॉडल मेटाकॉग्निटिव रीज़निंग की झलक दिखाता है

AGIは近づいている? Anthropic の Claude 3 Opus モデルはメタ認知推論の片鱗を示す

AGI가 가까워지고 있나요? Anthropic의 Claude 3 Opus 모델은 메타인지 추론의 희미한 빛을 보여줍니다

AGI está se aproximando? Modelo Claude 3 Opus da Anthropic mostra vislumbres de raciocínio metacognitivo

AGI становится ближе? Модель Claude 3 Opus от Anthropic демонстрирует проблески метакогнитивного мышления

AGI Yaklaşıyor mu? Anthropic'in Claude 3 Opus Modeli Üstbilişsel Akıl Yürütmenin Parıltılarını Gösteriyor

AGI có đang tiến gần hơn không? Mô hình Claude 3 Opus của Anthropic cho thấy những tia sáng của lý luận siêu nhận thức

AGI 越来越近了吗？ Anthropic 的 Claude 3 Opus 模型展现了元认知推理的曙光

As the festive season approaches, many of us eagerly anticipate the joy and warmth that Christmas brings. However, for individuals navigating the complexities of mental health diagnoses, this time of year can be a mixed bag of emotions. In this article, we delve deeper into the intersection of Christmas and mental health, exploring the challenges faced by those with various diagnoses and offering strategies for a more mindful and supportive holiday experience. 1. Depression and the Holiday Blues: Christmas can exacerbate feelings of loneliness and sadness, particularly for individuals dealing with depression. The pressure to partake in cheerful festivities can be overwhelming, leading to a sense of isolation for those who struggle with their mental health. It's essential to acknowledge and validate these emotions, fostering an environment that allows for open conversations about mental health. Strategies: - Establish realistic expectations and set boundaries for social engagements. - Prioritize self-care practices, such as adequate sleep, regular exercise, and healthy nutrition. - Reach out for support from friends, family, or mental health professionals. 2. Anxiety and the Season of Overwhelm: For individuals with anxiety disorders, the hustle and bustle of Christmas preparations can heighten stress levels. The demands of social gatherings, gift shopping, and event planning may trigger anxiety symptoms, ranging from restlessness to panic attacks. Strategies: - Plan and organize tasks well in advance to reduce last-minute stressors. - Practice mindfulness and relaxation techniques, such as deep breathing and meditation. - Communicate openly about your needs with loved ones and prioritize self-care during the holiday season. 3. Bipolar Disorder and the Highs and Lows: Christmas can be a challenging time for individuals with bipolar disorder, as the season's intensity may amplify mood swings. The pressure to be constantly festive may exacerbate manic episodes, while the contrast with the post-holiday period can lead to depressive feelings. Strategies: - Maintain a consistent daily routine, even during the holidays. - Monitor mood triggers and implement coping strategies as needed. - Collaborate with a mental health professional to adjust medication or therapy approaches for seasonal challenges. 4. Eating Disorders and the Festive Feast: The abundance of holiday feasts and social gatherings centered around food can be triggering for individuals with eating disorders. The emphasis on indulgence and celebration may exacerbate feelings of guilt and anxiety surrounding food. Strategies: - Plan ahead by establishing a supportive meal plan with the guidance of a healthcare professional. - Set boundaries around food-related events and communicate them to friends and family. - Seek encouragement and understanding from loved ones to create a nourishing, non-judgmental environment. As we celebrate the joy of Christmas, it's crucial to recognize and respect the diverse mental health challenges faced by individuals. By fostering open conversations, practicing empathy, and implementing supportive strategies, we can contribute to a more inclusive and mindful holiday season for everyone, regardless of their mental health diagnoses. Remember, the true spirit of Christmas lies in compassion, understanding, and the gift of connection. Also published . here

How to Navigate the Holidays: A Closer Look at Christmas and Mental Health Diagnoses

Several advancements this past week made headlines, and it looks like we are getting closer to the dream of becoming a multi-planetary species and discovering new technologies to help us get there. NASA recently achieved a significant milestone by streaming its first-ever video from deep space via laser, featuring a cat named Taters. The 15-second test video shows Taters chasing a laser pointer. This groundbreaking video was transmitted from an impressive distance of nearly 19 million miles away, which is about 80 times the distance between the Earth and the Moon. Abi Biswas, the project technologist for NASA's Deep Space Optical Communications (DSOC) experiment, that the project aims to enhance the streaming of data over long distances. This advancement is expected to support high-resolution science instruments and potentially aid human exploration of Mars. explained The video signal, which took 101 seconds to reach Earth, was sent on December 11th as part of a demonstration involving NASA's Psyche spacecraft, launched on October 13. This demonstration, according to NASA's Jet Propulsion Laboratory, was designed to transmit data at rates 10 to 100 times greater than current deep-space radio frequency systems. Remarkably, despite the vast distance, the video was transmitted faster than most broadband internet connections. An interesting aspect of this event is the choice of Taters for the video, drawing partial inspiration from Felix the Cat, a cartoon character used in 1928 for testing television transmissions. This enhanced streaming will assist astronauts in the future, and just in time as well because on Wednesday, Vice President Kamala Harris that NASA's Artemis program will include the participation of an international astronaut who will land on the moon's surface. announced This announcement marks a significant expansion of the United States' earlier promise to include international astronauts in future Artemis missions, which initially only involved flying them around the moon. The new development allows for an international astronaut to soon set foot on the lunar surface, joining the exclusive group of only 12 individuals who have achieved this feat to date. “ ” Harris during a meeting of the White House’s National Space Council in Washington, DC. Today, in recognition of the essential role that our allies and partners play in the Artemis program, I’m proud to announce that, alongside American astronauts, we intend to land an international astronaut on the surface of the moon by the end of the decade, said “The Artemis program is the most ambitious space exploration effort in generations. For the first time in more than half a century, the United States will return astronauts to the lunar surface. We will establish the first lunar base camp and the first station in lunar orbit — all of this in collaboration with our allies and partners,” she . said The Artemis program aims to establish a permanent, sustainable human presence on the lunar surface by the end of the decade. The skills and knowledge gained via this effort will help our species make the leap to Mars in the 2030s or 2040s, NASA officials have said, according to Space.com, an online source of space exploration, innovation, and astronomy news, chronicling (and celebrating) humanity's ongoing expansion across the final frontier. As part of its scientific endeavor, NASA’s Commercial Lunar Payload Services (CLPS) initiative allows NASA to send science investigations and technology demonstrations to the lunar surface. Under Artemis, NASA will study more of the Moon than ever before, and CLPS will demonstrate how NASA is working with commercial companies to achieve robotic lunar exploration. Private landers from Astrobotic and Intuitive Machines are set to launch, heralding a new phase in lunar exploration. These two NASA-funded space ventures are scheduled for back-to-back moon landings in early 2024. Slated to launch later next year, in November 2024, the Artemis II mission is set to be the first time humans will orbit the moon since the end of the Apollo program. The first mission to land on the moon — Artemis III — isn’t scheduled to launch until at least the end of 2025. However, that time frame has already been called into question as the space agency is keeping a close eye on the development of a SpaceX vehicle that will serve as the lander for Artemis III, ferrying astronauts down to the lunar surface. For its part, SpaceX is as well. making progress The company is gearing up for its third flight test of the massive Starship rocket just a month after its second launch. SpaceX is still awaiting regulatory approval from the Federal Aviation Administration for this third launch, following the FAA's classification of the second attempt as a "mishap" without injuries or public property damage. The company successfully conducted a static fire test of the next Starship, where its six Raptor engines ignited briefly without damaging the rocket or ground support equipment. Additionally, SpaceX has moved Booster 10 to the launch site at its Starbase facility in South Texas and placed it on the orbital launch mount, with a static fire test expected soon. After these tests, the Starship upper stage will likely be stacked on the booster, preparing the launch vehicle for "Integrated Flight Test 3." This third flight aims to further test Starship's capabilities. Exciting.

The Space Dream is Getting Closer

The internet is a fundamental part of our daily lives. From shopping online to accessing information and communicating with friends and colleagues, the web has become an integral tool for most people. However, it's essential to recognize that not everyone experiences the web in the same way. Many individuals face challenges when navigating websites, and this is where the Web Accessibility Initiative comes into play. Understanding Web Accessibility Initiative The Web Accessibility Initiative (WAI) is a comprehensive program developed by the World Wide Web Consortium (W3C) to ensure that the web is accessible to all users, regardless of their disabilities. It strives to make the internet a more inclusive and user-friendly space for everyone, including those with visual, auditory, motor, and cognitive impairments. Why is Web Accessibility Important? Web accessibility is vital because it promotes digital equality and inclusivity. Inaccessible websites can create significant barriers for people with disabilities, hindering their ability to access information, services, and products online. By adhering to the guidelines and principles set forth by the Web Accessibility Initiative, web developers can create websites that are usable by a broader audience, thereby extending their reach and impact. Key Components of Web Accessibility
To get a better understanding of the Web Accessibility Initiative, let's delve into its key components: Web Content Accessibility Guidelines (WCAG) WCAG is the foundation of the Web Accessibility Initiative. It provides a set of guidelines and success criteria that web developers should follow to create accessible web content. The guidelines cover various aspects, including: Perceivable: Ensuring that all information and user interface components can be perceived.
Operable: Making sure that the interface is operable by any user.
Understandable: Providing content that is easily understandable.
Robust: Creating content that can be reliably interpreted by a wide variety of user agents, including assistive technologies. These guidelines help web developers make their websites more accessible by providing clear, concise instructions on what to do and what to avoid. Accessible Rich Internet Applications (ARIA) ARIA is a set of attributes that can be added to HTML elements to improve their accessibility for users with disabilities. It enhances the functionality and interactivity of web content for individuals who rely on assistive technologies like screen readers. ARIA roles, states, and properties provide additional information to these technologies, making web applications more understandable and navigable. User Agent Accessibility Guidelines (UAAG) User agents are software applications that render web content, such as web browsers and assistive technologies. UAAG defines the requirements for user agents to ensure they provide accessible user interfaces and render web content correctly. By following these guidelines, user agents can better support people with disabilities in accessing the web. Web Accessibility Initiative in Practice Now that we understand the components of the Web Accessibility Initiative, let's explore how it works in practice: Web developers play a crucial role in implementing web accessibility. They need to follow the WCAG guidelines, integrate ARIA attributes where necessary, and ensure that the website is usable by a diverse audience. Design choices, color contrasts, and text alternatives for images are just a few examples of factors that developers must consider to create an accessible web presence. Design and Development Testing and evaluation are critical to ensuring web accessibility. Developers and quality assurance teams can use various tools and assistive technologies to assess the accessibility of a website. These tools can help identify issues and provide recommendations for improvements. Testing and Evaluation Web Accessibility Initiative promotes ongoing education and training to raise awareness about the importance of web accessibility. It offers resources, training materials, and documentation for developers, designers, and content creators to enhance their knowledge and skills in making the web more inclusive. Education and Training The Benefits of Web Accessibility Embracing the Web Accessibility Initiative offers several advantages for businesses and organizations: By making your website accessible, you open doors to a more extensive and diverse audience, including people with disabilities. This can lead to increased traffic and potential customers. Expanded Audience In many regions, there are legal requirements to ensure web accessibility. Compliance with these regulations helps protect your organization from potential legal issues. Legal Compliance Demonstrating a commitment to web accessibility can enhance your brand's reputation and demonstrate social responsibility. Enhanced Reputation References To learn more about the Web Accessibility Initiative and its importance, you can explore the following references: Web Accessibility Initiative (WAI) - W3C Web Content Accessibility Guidelines (WCAG) Overview Accessible Rich Internet Applications (ARIA) - W3C User Agent Accessibility Guidelines (UAAG) - W3C In conclusion, the Web Accessibility Initiative is a pivotal program that works to make the Internet accessible to everyone, regardless of their abilities. It offers guidelines, best practices, and resources to help web developers create inclusive websites. By embracing web accessibility, businesses and organizations can expand their reach, enhance their reputation, and, most importantly, contribute to a more inclusive online environment.

A Closer Look at the Web Accessibility Initiative

FTC v. Amazon Court Filing, retrieved on Sep 26, 2023, is part of . You can jump to any part in this filing . This is part 1 of 80. HackerNoon’s Legal PDF Series here A. Amazon's First-Party Retail And Third-Party Marketplace Business Units 67. Amazon's First-Party Retail And Third-Party Marketplace Business Units Amazon began as an online bookstore in 1994 and rapidly expanded into new product categories: first DVDs and CDs, then electronics and toys, and then nearly everything. In 2020, Amazon sold almost (redacted) unique products across virtually every conceivable category to U.S. consumers. 68. Amazon originally sold goods to shoppers by purchasing items wholesale and reselling them on its website. Amazon calls its wholesale suppliers "vendors." Today, Amazon continues to sell a wide range of products through this type of vendor-retailer relationship, from laundry detergent to sports equipment. 69. Amazon also sells its own private label goods. These range from devices like Amazon's Kindle e-reader or Ring doorbell, to consumer products like batteries sold under the "Amazon Basics" label, to products without any clear· Amazon affiliation, such as dietary supplements sold under the "Revly" label. 70. These two components, vendor-retailer and private label, make up Amazon's first-party retail business unit, which Amazon refers to collectively as Amazon "Retail." 71. Amazon also runs what it calls its "Marketplace," where other companies can sell products directly to shoppers through its online store. Amazon calls third-party companies that sell on Amazon "sellers," and refers to sales by sellers as "Marketplace" sales. 72. Amazon charges sellers four primary fees to sell on its Marketplace. First, Amazon requires sellers to pay a selling fee, which can be a monthly fee or a fee for each item sold. Second, Amazon charges all sellers a commission or "referral fee" based on the price of each item sold on Amazon. Third, Amazon charges sellers for the use of Amazon's fulfillment and delivery services. Forth, Amazon charges sellers for advertising services. While Amazon also charges sellers. As a practical matter, most sellers must pay these four fees to make a significant volume of sales on Amazon. 73. Amazon estimated that in 2022, it would take (redacted)% of all sales revenue earned by sellers who use its fulfillment service. 74. The Marketplace accelerated Amazon's growth by allowing it to exponentially expand the selection of products on Amazon without having to carry the risks of unsold inventory. Sellers, who range from small businesses that offer a single product to multinational firms that sell thousands of products, ultimately bear that risk. As of the first quarter of 2021, there were over (redacted) active sellers on Amazon's U.S. Marketplace. 75. Amazon touts to its investors that sellers on the Marketplace are "a key 20 contributor to the selection offered" to Amazon shoppers. Sellers offer a huge variety of items for sale, from laptop computers to harnesses for walking pet chickens, complete with bowtie. In 2020, sellers offered more than (redacted)% of the unique items available for sale on Amazon. Sellers' products make up a growing majority of Amazon unit sales- 60% in the second quarter of 2023, up from 55% in 2021. 76. Amazon's online superstore unites its Retail and Marketplace rums, with products intermixed and presented to the public simultaneously and side-by-side. To a shopper browsing on Amazon, there are no obvious differences between the types of listings, nor is there a way to regularly shop for products sold only by Amazon Retail or Amazon Marketplace. 77. Amazon has achieved unprecedented scale. In 2021, goods worth more than (redacted) were sold through Amazon's U.S. online store. That amount is larger than the 2021 gross domestic product of (redacted) countries. 78. Amazon achieved this astonishing scale in part by combining its Retail and Marketplace arms. Amazon's product selection includes popular· and frequently pm-chased items and a "long tail" made up of an immense variety of less-frequently purchased products. Products offered by sellers on Amazon's Marketplace contribute substantially to that "long tail." More generally, Amazon’s sellers dramatically increase Amazon’s product selection, which draws more shoppers to Amazon, which, in turn, attracts more sellers. 79. Sellers have also made the Marketplace enormously profitable for Amazon. Amazon's internal documents show that profits from its U.S. Marketplace totaled more than (redacted) in 2021-nearly (redacted)% of its total reported net income for that year. Continue Reading . Here About HackerNoon Legal PDF Series: We bring you the most important technical and insightful public domain court case filings. This court case 2:23-cv-01495 retrieved on October 2, 2023, from is part of the public domain. The court-created documents are works of the federal government, and under copyright law, are automatically placed in the public domain and may be shared without legal restriction. ftc.gov

A Closer Look at Amazon's Growing  E-commerce Monopoly

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The TechBeat: August Rollups Data Analysis: A Closer Look at Transaction Activity (10/3/2023)

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The TechBeat: August Rollups Data Analysis: A Closer Look at Transaction Activity (10/1/2023)

As of today, the narrative of Rollups has gradually become ingrained in people's minds. On one hand, it inherits the security, user base, and ecosystem of the Mainnet while reducing transaction fees and effectively boosting performance, greatly enhancing the user experience. On the other hand, the business model of Layer2, such as transaction fee commissions, is becoming increasingly clear. As the primary direction for Layer2 scaling, the Rollup track has seen frequent developments lately: Linea announced the opening of Alpha access to the Mainnet, Base officially launched its Mainnet, zkSync's bridge transaction user participation exceeded 2 million... To gain a better understanding of the overall development of the Layer2 track, Opside has compiled statistics on some of the mainstream Layer2 solutions on the market (Polygon, Arbitrum, Optimism, zkSync, Linea, Base, etc.) and conducted an analysis of various dimensions. Below are the specific data performances of major Rollups in August: Transaction Activity In terms of transaction activity, zkSync stands out with an astonishing average daily transaction count of 929,445. This indicates that zkSync's ecosystem has achieved significant success in attracting users and transactions. On the other hand, Metis shows relatively weaker performance with an average daily transaction count of only 116,017, which could be attributed to Metis' high transaction fees. User Costs From a user cost perspective, Metis' users seem to incur relatively high gas fees, with an average daily GasFee of 17.001 Gwei. In stark contrast, Optimism has very low user costs, with an average daily GasFee of only 0.131 Gwei. This could make Optimism more attractive, especially for users looking to reduce transaction costs. However, Optimism has not found an appropriate balance yet. Maybe the low GasFee has led to losses. Performance of revenues and expenses In terms of revenues, Metis shows outstanding performance with an average daily revenue of 62.591 ETH, which is the highest among the analyzed solutions. However, Optimism leads in terms of expenditure, with a monthly total expenditure of 1,272.512 ETH. This may require Optimism to further optimize its expenditure strategy to improve net revenues. Net Income Metis also performs well in net income, with an average daily net income of 61.617 ETH and a monthly total net income of 1,910.115 ETH. In contrast, Optimism has a negative net income, with an average daily net income of -26.050 ETH and a monthly total net income of -807.558 ETH. This calls for measures to improve net income for Optimism to maintain its sustainability, such as appropriately increasing GasFee.

August Rollups Data Analysis: A Closer Look at Transaction Activity

Análisis de datos acumulativos de agosto: una mirada más cercana a la actividad de las transacciones

Analyse des données des cumuls d'août : un examen plus approfondi de l'activité des transactions

अगस्त रोलअप डेटा विश्लेषण: लेन-देन गतिविधि पर एक नज़दीकी नज़र

8 月のロールアップ データ分析: トランザクション アクティビティを詳しく見る

Análise de dados de rollups de agosto: uma análise mais detalhada da atividade de transação

Phân tích dữ liệu tổng hợp tháng 8: Xem xét kỹ hơn về hoạt động giao dịch

八月汇总数据分析：仔细观察交易活动

In the vast expanse of the digital realm, data is the lifeblood that sustains, instructs, and enriches countless applications. Central to the management and efficient use of this data are databases, and among them, embedded databases have carved out a distinctive niche. An embedded database is essentially a database management system (DBMS) that is tightly integrated within an application's software. Unlike standalone databases which run on dedicated servers and cater to multiple applications, embedded databases run within the application itself, ensuring a seamless data flow with minimal setup and external dependencies. The importance of embedded databases in modern application design is multifold. Firstly, their self-contained nature means they can operate without the overhead of server maintenance, making deployment and distribution simpler. This is especially crucial for applications that need to be agile and responsive, devoid of external bottlenecks. Secondly, with data being a crucial asset, an embedded approach often brings with it enhanced security, as data doesn't have to traverse over networks or interact with external systems. Furthermore, the use cases for embedded databases span a wide spectrum. From powering local data storage on mobile apps, to being the heart of IoT devices collecting real-time metrics, and even serving as the foundational data store for large desktop software, embedded databases have proven to be versatile, efficient, and resilient. As we journey through this article, we'll delve deeper into three of the top embedded databases that are shaping the industry: SQLite, RocksDB, and DuckDB, uncovering what makes each of them stand out in their own right. SQLite SQLite's origins can be traced back to the early 2000s when it was conceived by D. Richard Hipp. The initial motivation wasn't to create a widely-used database, but rather to serve a specific need in a software project Hipp was working on. The aim was to develop a no-fuss, serverless, zero-configuration, and self-contained database engine, and SQLite was the result. : SQLite is publicly released as version 1.0. It stands out by virtue of its self-contained nature, where an entire relational database is stored in a single cross-platform disk file. August, 2000 : Version 2.0 was released with improved storage with a custom B-tree implementation, adding transaction capability. September, 2001 : SQLite 3, the version most widely used today, was introduced. It brought in many improvements over the previous versions, including a new file format which offers better performance and support for more SQL features. This version set the stage for SQLite's rise to ubiquity. June, 2004 SQLite is a powerhouse for developers when it comes to its SQL language capabilities. It understands most of the standard SQL language, but it does while at the same time adding a few features of its own. It provides extensive support for upsert operations via the "INSERT ON CONFLICT" clause, giving developers flexibility in handling unique constraint violations. Subqueries are also well-supported, allowing for complex nested operations within SELECT, INSERT, UPDATE, and DELETE statements. Additionally, SQLite permits the creation of user-defined functions and aggregates, granting developers the ability to tailor the SQL environment to specific needs. Furthermore, its robust set of built-in functions, from string manipulation to date-time operations, ensures that developers have a rich toolkit to perform varied transformations and computations directly within SQL queries. omit some features Over the years, SQLite's reputation as a reliable and efficient database system grew. It has been famously adopted in various applications and platforms. From web browsers like Firefox and Chrome storing bookmarks and web history, to mobile operating systems like iOS and Android powering app data storage, SQLite's footprint is vast. Today, SQLite prides itself on being the most widely deployed and used database engine. Its public domain source code, rigorous testing, and commitment to reliability have made it a staple for developers across the globe. RocksDB RocksDB, a high-performance embedded database tailored for key-value data, was birthed out of the vibrant ecosystem of open-source projects at Facebook. It is essentially an evolution, aimed at addressing the unique storage needs of the tech giant. : RocksDB was created by Dhruba Borthakur as a fork of Google's LevelDB optimized to exploit multi-core processors (CPUs), and make efficient use of fast storage, such as solid-state drives (SSD), for input/output (I/O) bound workloads. It is based on a log-structured merge-tree (LSM tree) data structure. The primary motivation behind RocksDB was to extend LevelDB's capabilities to meet the performance, efficiency, and flexibility demands of Facebook's massive real-time applications. April, 2012 : RocksDB was open-sourced by Facebook, allowing a community of developers and industries to contribute, adapt, and integrate it into their specific use cases. The decision to open-source also catalyzed a flurry of enhancements and adaptations, driven by the collective wisdom of the community. November, 2013 Over the subsequent years, RocksDB rapidly evolved. It introduced features like optimized data compaction, tunable write-ahead logs, and enhancements that provided significant performance boosts. All these were designed to cater to applications that demanded low-latency database reads and writes, especially in large-scale, real-time environments. RocksDB's design makes it adaptable beyond just key-value storage; its pluggable framework allows it to serve as a storage engine for other higher-level database systems. For example, such well known systems as Apache Flink, TiDB and YugabyteDB use RocksDB as their embedded storage engine. Today, RocksDB is recognized as a robust, high-speed storage solution that powers various products, both within and outside Facebook. From real-time analytics to search infrastructure and messaging platforms, its adaptability and performance have made it a go-to choice for many in the industry. DuckDB DuckDB stands as an intriguing testament to the evolving needs of analytical data processing in a modern context. This analytical data management system, tailored for embedded analytics, is a fairly recent entrant into the database realm but has quickly carved out its own niche. : The initial foundations of DuckDB began taking shape around this time. Unlike many other databases focused on transactional workloads, DuckDB was specifically architected to cater to analytical queries, all within an embedded context. The creators, Mark Raasveldt and Hannes Mühleisen, aimed to design a system that provided efficient analytical data processing without the need for an external system or heavy infrastructure. 2018-2019 DuckDB's design was heavily influenced by the MonetDB, a column-store database known for its efficient handling of analytical workloads. However, where MonetDB was a full-fledged server, DuckDB was intended to be lightweight and embedded. One of the standout features of DuckDB was its ability to handle vectorized query execution. This method processes data in chunks or "vectors" rather than row by row, which significantly boosts query performance, especially for analytical operations. DuckDB also garnered attention for its ease of integration. Given its embedded nature, developers could easily incorporate it into various software applications, from Python data science platforms to web-based analytics tools. : The popularity and adoption of DuckDB have been on the rise. The database system has been praised for its ability to combine the speed of analytical databases with the simplicity and low overhead of embedded systems. 2020 and beyond As of the last update, DuckDB continues to evolve, with an active community contributing towards its growth and enhancements. The database has found its place in diverse applications, from research projects to commercial platforms, attesting to its flexibility and robustness. Conclusion The landscape of embedded databases has evolved significantly over the past two decades, driven by the demands of diverse applications, from mobile apps to cutting-edge research platforms. As we've explored, SQLite, RocksDB, and DuckDB each represent a unique blend of design philosophies, optimizations, and application scenarios. Whether you're a developer seeking a lightweight storage solution or a researcher looking for efficient analytical processing, the world of embedded databases offers a myriad of options to cater to your needs. The journey, however, doesn't end here. As technology continues to advance and the data deluge grows, the evolution of embedded databases will undoubtedly march forward, ushering in new optimizations, features, and perhaps even challenges. For those keen on diving deeper into each of these powerful tools, the following resources provide comprehensive insights: offers a wealth of information on its features, use cases, and optimization tips. SQLite's official documentation For a thorough exploration of RocksDB's capabilities, Facebook's is a treasure trove of articles and updates. official RocksDB blog To delve deeper into DuckDB's design philosophy and applications, the is an excellent starting point. DuckDB project's GitHub page In closing, the realm of embedded databases, with its blend of versatility and efficiency, promises to remain a cornerstone of application development and data management in the years to come. Embracing and understanding these tools is not just beneficial - it's essential for anyone keen on staying ahead in the rapidly evolving tech landscape.

A Closer Look at the Top 3 Embedded Databases: SQLite, RocksDB, and DuckDB

United States Of America. v. Microsoft Corporation Court Filing by Thomas Penfield Jackson, November 5, 1999, is part of . You can jump to any part in this filing . This is part 4 of 58. HackerNoon’s Legal PDF Series here A. Demand Substitutability 1. Server Operating Systems 19. Consumers could not turn from Intel-compatible PC operating systems to Intel-compatible server operating systems without incurring substantial costs, since the latter type of system is sold at a significantly higher price than the former. A consumer intent on acquiring a server operating system would also have to buy a computer of substantially greater power and price than an Intel-compatible PC, because server operating systems generally cannot function properly on PC hardware. The price of an Intel-compatible PC operating system accounts for only a very small percentage of the price of an Intel-compatible PC system. Thus, even a substantial increase in the price of an Intel-compatible PC operating system above the competitive level would result in only a trivial increase in the price of an Intel-compatible PC system. Very few consumers would purchase expensive servers in response to a trivial increase in the price of an Intel-compatible PC system. Furthermore, a consumer would not obtain a satisfactory substitute for an Intel-compatible PC operating system even if he purchased a server, since server operating systems lack the features — and support for the breadth of applications — that induce users to purchase Intel-compatible PC operating systems. Continue reading . here About We bring you the most important technical and insightful public domain court case filings. HackerNoon Legal PDF Series: This court case Civil Action No. 98-1232 (TPJ) retrieved on 1-19-2023, from is part of the public domain. The court-created documents are works of the federal government, and under copyright law, are automatically placed in the public domain and may be shared without legal restriction. justice.gov

The United States of America v. Microsoft: Taking a Closer Look at Server Operating Systems

The Hypersonic Drone Market: How the Axis of Innovation Is Forming Around It

In my latest letter, Sell in May and Go Away, I highlighted that we were heading for the low liquidity season of the year and that the crypto markets would need a pause before trending higher. At this moment in time, I think the sluggish summer may finally be coming to an end. Uncertainty regarding the U.S. elections is in front of us, and given the many events that unfolded this month, I think we can expect plenty more volatility where investors will be “trading the election” until we see the results in November. Trump Going to the Oval Office? Trump is likely to become the next president. Following the assassination attempt, prediction markets put his likelihood at 71%, and now with Biden’s withdrawal, that has fallen to a comfortable 60%, with Kamala Harris looking like the second most obvious choice with a 38% probability currently. Digital Assets is the Talk of Town What’s interesting about this election is that digital assets have become a topic for candidates to discuss. Apparently, the political elite has finally understood that the +50M crypto holders in America represent a big voter base. This weekend, Trump and R. Kennedy Jr. are both speaking at the Bitcoin2024conference. Kamala Harris was also expected to speak there but declined the opportunity just a few days ago.Another interesting aspect is Trump’s choice of running mate, JD Vance. JD Vance is a self-proclaimed BTC holder, has been a strong proponent of the crypto industry in the Senate, and one of Gary Gensler's most vocal critics in recent years. A bitcoiner on the running card. How about that? Is it Finally Time to Lower the Rates? It’s now been a year since the Fed raised its benchmark rate to between 5.25% and 5.5%, holding this target range steady to date. In the meantime, Jerome Powell has said again and again that rates would not be lowered before something would either break or before the Fed would have been convinced inflation rates would trend lower towards the target rate of 2%. The most recent economic data signals that the Fed could soon start cutting rates: The Fed is getting closer to its 2% inflation target. In June, the monthly CPI fell by 0.1%, while the annual CPI rose by 3%. The U.S. economy is finally softening. GDP growth slowed to an annual rate of 1.4% in Q1 2024, down from 3.4% in the previous quarter. The labor market is also cooling down; June’s unemployment rate spiked to 4.1%, the highest it has been since November 2021. Additionally, Jerome Powell appeared on Capitol Hill this month and warned that “reducing policy restraint too late or too little could unduly weaken economic activity and employment.” Is the “higher for longer” regime coming to an end? It is still quite a balancing act for the Fed, but it seems inevitable that something has to move sooner rather than later. Currently, the market is predicting a 95.3% chance of a rate cut in September’s FOMC meeting. Bitcoin Remains Resilient Despite Sell-offs Bitcoin’s price has remained range-bound between $60K and $70K for most of the summer despite the drying liquidity from Bitcoin ETFs, which had propelled the price from lows of $42K before the approval to record highs of $73K in March. But what’s more remarkable is BTC’s resilience following the recent $2.87 billion sell-off by Germany’s Saxony state. That said, there's a risk of additional selling pressure. Mt. Gox, the defunct crypto exchange, has started its repayment plan, which aims to reimburse creditors around $9 billion worth of Bitcoin and Bitcoin Cash. 140,000 BTC; this is worth over $9 billion at the current market price. So far, over 40% of the repayments have already been distributed to the creditors. On the brighter side, repayments in-kind does not equal selling pressure as creditors may decide to HODL their BTC. On-chain data shows that BTC withdrawals on Kraken spiked after the exchange completed distributing its share of allocated repayments. This is a sign that a good number of Mt. Gox creditors could be moving their repayments to cold wallets for long-term HODLing. Personally, I remain optimistic that BTC’s price will trend higher in H2 based on its current resilience amid the much-awaited Mt. Gox repayments, which most had predicted would be a huge sell-off event. Additionally, there are some macro and industry-specific factors that could be catalysts in sustaining the current price levels or pushing BTC higher: A good number of the creditors might decide to HODL onto their BTC, causing only short-term downward pressure on BTC’s price. Once the uncertainty over Mt. Gox repayments is over, there is no big expected selling pressure. There is a high chance that the Fed will cut rates in September, likely triggering a rally in risk-on assets. Liquidity is gradually returning to the market. Blackrock’s Bitcoin Spot ETF recently recorded a daily net inflow of $526 million, the largest since March 13th. The crypto market could soon play catch-up with the S&P 500, Nasdaq, and Gold, which showed strength in Q2 while BTC lagged over the past three months. The crypto markets are favoring the Republican Party, and currently, it remains likely that Trump will take office. In my latest letter, Sell in May and Go Away , I highlighted that we were heading for the low liquidity season of the year and that the crypto markets would need a pause before trending higher. At this moment in time, I think the sluggish summer may finally be coming to an end. Sell in May and Go Away Sell in May and Go Away Sell in May and Go Away Uncertainty regarding the U.S. elections is in front of us, and given the many events that unfolded this month, I think we can expect plenty more volatility where investors will be “trading the election” until we see the results in November. Trump Going to the Oval Office? Trump is likely to become the next president. Following the assassination attempt, prediction markets put his likelihood at 71%, and now with Biden’s withdrawal, that has fallen to a comfortable 60%, with Kamala Harris looking like the second most obvious choice with a 38% probability currently. Digital Assets is the Talk of Town What’s interesting about this election is that digital assets have become a topic for candidates to discuss. Apparently, the political elite has finally understood that the +50M crypto holders in America represent a big voter base. +50M crypto holders +50M crypto holders This weekend, Trump and R. Kennedy Jr. are both speaking at the Bitcoin2024 conference. Kamala Harris was also expected to speak there but declined the opportunity just a few days ago. Another interesting aspect is Trump’s choice of running mate, JD Vance. JD Vance is a self-proclaimed BTC holder, has been a strong proponent of the crypto industry in the Senate, and one of Gary Gensler's most vocal critics in recent years. Bitcoin2024 A bitcoiner on the running card. How about that? Is it Finally Time to Lower the Rates? It’s now been a year since the Fed raised its benchmark rate to between 5.25% and 5.5%, holding this target range steady to date. In the meantime, Jerome Powell has said again and again that rates would not be lowered before something would either break or before the Fed would have been convinced inflation rates would trend lower towards the target rate of 2%. The most recent economic data signals that the Fed could soon start cutting rates: could The Fed is getting closer to its 2% inflation target. In June, the monthly CPI fell by 0.1%, while the annual CPI rose by 3%. The Fed is getting closer to its 2% inflation target. In June, the monthly CPI fell by 0.1%, while the annual CPI rose by 3%. The U.S. economy is finally softening. GDP growth slowed to an annual rate of 1.4% in Q1 2024, down from 3.4% in the previous quarter. The U.S. economy is finally softening. GDP growth slowed to an annual rate of 1.4% in Q1 2024, down from 3.4% in the previous quarter. The labor market is also cooling down; June’s unemployment rate spiked to 4.1%, the highest it has been since November 2021. The labor market is also cooling down; June’s unemployment rate spiked to 4.1%, the highest it has been since November 2021. The labor market is also cooling down; June’s unemployment rate spiked to 4.1%, the highest it has been since November 2021. Additionally, Jerome Powell appeared on Capitol Hill this month and warned that “ reducing policy restraint too late or too little could unduly weaken economic activity and employment. ” reducing policy restraint too late or too little could unduly weaken economic activity and employment. Is the “higher for longer” regime coming to an end? It is still quite a balancing act for the Fed, but it seems inevitable that something has to move sooner rather than later. Currently, the market is predicting a 95.3% chance of a rate cut in September’s FOMC meeting. Bitcoin Remains Resilient Despite Sell-offs Bitcoin’s price has remained range-bound between $60K and $70K for most of the summer despite the drying liquidity from Bitcoin ETFs, which had propelled the price from lows of $42K before the approval to record highs of $73K in March. But what’s more remarkable is BTC’s resilience following the recent $2.87 billion sell-off by Germany’s Saxony state . Germany’s Saxony state Germany’s Saxony state That said, there's a risk of additional selling pressure. Mt. Gox, the defunct crypto exchange, has started its repayment plan, which aims to reimburse creditors around $9 billion worth of Bitcoin and Bitcoin Cash. 140,000 BTC; this is worth over $9 billion at the current market price. So far, over 40% of the repayments have already been distributed to the creditors. On the brighter side, repayments in-kind does not equal selling pressure as creditors may decide to HODL their BTC. On-chain data shows that BTC withdrawals on Kraken spiked after the exchange completed distributing its share of allocated repayments. This is a sign that a good number of Mt. Gox creditors could be moving their repayments to cold wallets for long-term HODLing. Personally, I remain optimistic that BTC’s price will trend higher in H2 based on its current resilience amid the much-awaited Mt. Gox repayments, which most had predicted would be a huge sell-off event. Additionally, there are some macro and industry-specific factors that could be catalysts in sustaining the current price levels or pushing BTC higher: A good number of the creditors might decide to HODL onto their BTC, causing only short-term downward pressure on BTC’s price. A good number of the creditors might decide to HODL onto their BTC, causing only short-term downward pressure on BTC’s price. Once the uncertainty over Mt. Gox repayments is over, there is no big expected selling pressure. Once the uncertainty over Mt. Gox repayments is over, there is no big expected selling pressure. There is a high chance that the Fed will cut rates in September, likely triggering a rally in risk-on assets. There is a high chance that the Fed will cut rates in September, likely triggering a rally in risk-on assets. Liquidity is gradually returning to the market. Blackrock’s Bitcoin Spot ETF recently recorded a daily net inflow of $526 million, the largest since March 13th. Liquidity is gradually returning to the market. Blackrock’s Bitcoin Spot ETF recently recorded a daily net inflow of $526 million, the largest since March 13th. The crypto market could soon play catch-up with the S&P 500, Nasdaq, and Gold, which showed strength in Q2 while BTC lagged over the past three months. The crypto market could soon play catch-up with the S&P 500, Nasdaq, and Gold, which showed strength in Q2 while BTC lagged over the past three months. The crypto markets are favoring the Republican Party, and currently, it remains likely that Trump will take office. The crypto markets are favoring the Republican Party, and currently, it remains likely that Trump will take office.

Here's Why It’s Time to Wake Up Again…

Holodeck Heroes: Building AI Companions for the Final Frontier

Authors:
(1) Zhongtang Luo, Purdue University (luo401@purdue.edu);
(2) Rohan Murukutla, Supra (r.murukutla@supraoracles.com);
(3) Aniket Kate, Purdue University / Supra (aniket@purdue.edu). Table of Links Abstract and I. Introduction II. Expectations of Blockchain Accessibility III. Approach I: Maintain a Ledger Locally - Run a Full Node IV. Approach II: Query a Third-Party Ledger-Node-As-A-Service (NAAS) V. Approach III: Light Node - External Query & Local Verification VI. Concluding Remark and References Abstract—While much research focuses on different methods to secure blockchain, information on the chain needs to be accessed by end-users to be useful. This position paper surveys different ways that end-users may access blockchains. We observe that between the two extremes of running a full node and fully utilizing a trusted third-party service, many solutions regarding light nodes are emerging. We analyze these solutions based on three basic properties of web communication: integrity, availability and privacy. We conclude that currently, the best way to access a blockchain while maintaining these three properties is still to run a full node. We consider it essential that future blockchain accessibility services should be built while considering these three expectations. I. INTRODUCTION A blockchain is a group of nodes trying to maintain a publicly verifiable ledger of transactions protected from tampering. After its first proposal as Bitcoin [41] in 2009, blockchains have gained much popularity as financial instruments. The success of most well-known blockchains, such as Bitcoin and Ethereum [20] can largely be attributed to their decentralized nature and their capabilities to handle complex transactions with advanced cryptographic primitives. With currently a large market, blockchains have the potential to become a leading innovation in the finance and e-commerce sectors in the 21st century. Much existing blockchain infrastructure research and innovation focus on secure and efficient ways for participating nodes to maintain the public ledger (known as a layer-1 protocol). However, we note that fetching information from a well-maintained ledger is also a non-trivial issue. Ensuring that blockchains stay accessible to every user is essential if blockchains are to play a bigger role in everyday life—a public ledger is, by definition, only useful as long as people can interact with it. Given the recent growing public interest in blockchains, more users are interacting with blockchains every month, with as many as 875,000 transactions a day for popular blockchains such as Ethereum [20]. Trying to extract useful information from a flood of transactions requires powerful hardware for even a standard blockchain user who does not engage in profit-generating behavior (like mining), and it appears that the incentive mechanism in most blockchains is not equipped to deal with the issue. In most blockchain protocols, such as Bitcoin and Ethereum, participating nodes (miners in proof-of-work systems and validators in proof-of-stake systems) are incentivized to maintain the ledger by earning a small fee when proposing a new block to the ledger. While participating nodes in these blockchain protocols are incentivized to collect transactions and broadcast raw blocks to ensure their profit, they are not incentivized to publish refined information about the ledger they maintain. Consider these two examples: (1) A user wants to know how many coins there are in their Bitcoin wallet. (2) A user wants to know the current status of a smart contract they want to execute. Similar to these examples, most information users want to know is not directly related to the raw blocks that miners and validators publish. The users may entrust their assets fully to a third-party exchange and obtain information from the exchange, but the approach is significantly risky as evidenced by the recent FTX collpase [31]. Therefore, blockchain users need to devise a method to extract such information from blocks, either through some computation power that they own or by relying on a third-party service provider. In this paper, we compare the two current methods in practice that users adopt to obtain refined information from blockchains. One method involves running a full node locally. This method is usually capable of extracting much information from the blockchain without external reliance. In some cases though, additional indices are kept to ensure a faster query, such as Ethereum archive nodes and Solana RPC nodes. The other method is to rely on a third-service provider. We notice the trend that as the cost of running a full node grows, especially in Ethereum, many users are turning to third-party services, which carry their own security risks. We observe that running a full node and fully utilizing a trusted third-party service represent two extremes regarding blockchain accessibility: one with minimal reliance and maximal hardware requirement and one with maximal reliance and minimal hardware requirement. We also notice that when the required data on the blockchain is specific and limited, like when the users only care about one address that they own, specific wallet software is available to the users. While some of the wallet software queries an external node directly for data, others may download a portion of the blockchains and directly analyze it for the information the users care about. We categorize the software as specific light nodes. Meanwhile, we outline a recent trend in realizing a universal light node that can provide any information to users, not just one address [12], such as the one proposed by Ethereum [24]. Current research also includes so-called ultralight nodes, such as Flyclient [10], that step closer to relying on a third-party service that provides additional context for verification (also known as a prover in this context) than traditional light nodes that rely only on full nodes. Figure 1 shows a list of different methods to access blockchains. We think that amid many ways to access blockchains, it is still important to examine the basics of any web service: integrity, availability, and privacy. The blockchain itself is a technology of decentralization, yet too much reliance on a small number of third parties goes against this premise. Without a method to verify the correctness of data, integrity may be compromised if the said third parties provide incorrect data. With too much dependence on selected third parties to provide accessibility, availability may be impacted if they are unable or unwilling to provide service. Privacy is also a concern that needs addressing when querying any third party. We examine existing protocols in the market and find that many of them may be flawed in at least one of these aspects. Currently, the best way to access a blockchain while maintaining integrity, availability and privacy is still to run a full node locally. We consider it important to pay attention to these three aspects when designing any protocol to interact with blockchains to ensure functionality. This paper is available on arxiv under CC BY-NC-ND 4.0 DEED license. Authors: (1) Zhongtang Luo, Purdue University (luo401@purdue.edu); (2) Rohan Murukutla, Supra (r.murukutla@supraoracles.com); (3) Aniket Kate, Purdue University / Supra (aniket@purdue.edu). Authors: Authors: (1) Zhongtang Luo, Purdue University (luo401@purdue.edu); (2) Rohan Murukutla, Supra (r.murukutla@supraoracles.com); (3) Aniket Kate, Purdue University / Supra (aniket@purdue.edu). Table of Links Abstract and I. Introduction Abstract and I. Introduction II. Expectations of Blockchain Accessibility II. Expectations of Blockchain Accessibility III. Approach I: Maintain a Ledger Locally - Run a Full Node III. Approach I: Maintain a Ledger Locally - Run a Full Node IV. Approach II: Query a Third-Party Ledger-Node-As-A-Service (NAAS) IV. Approach II: Query a Third-Party Ledger-Node-As-A-Service (NAAS) V. Approach III: Light Node - External Query & Local Verification V. Approach III: Light Node - External Query & Local Verification VI. Concluding Remark and References VI. Concluding Remark and References Abstract—While much research focuses on different methods to secure blockchain, information on the chain needs to be accessed by end-users to be useful. This position paper surveys different ways that end-users may access blockchains. We observe that between the two extremes of running a full node and fully utilizing a trusted third-party service, many solutions regarding light nodes are emerging. We analyze these solutions based on three basic properties of web communication: integrity, availability and privacy. We conclude that currently, the best way to access a blockchain while maintaining these three properties is still to run a full node. We consider it essential that future blockchain accessibility services should be built while considering these three expectations. Abstract —While much research focuses on different methods to secure blockchain, information on the chain needs to be accessed by end-users to be useful. This position paper surveys different ways that end-users may access blockchains. We observe that between the two extremes of running a full node and fully utilizing a trusted third-party service, many solutions regarding light nodes are emerging. We analyze these solutions based on three basic properties of web communication: integrity, availability and privacy. We conclude that currently, the best way to access a blockchain while maintaining these three properties is still to run a full node. We consider it essential that future blockchain accessibility services should be built while considering these three expectations. Abstract I. INTRODUCTION A blockchain is a group of nodes trying to maintain a publicly verifiable ledger of transactions protected from tampering. After its first proposal as Bitcoin [41] in 2009, blockchains have gained much popularity as financial instruments. The success of most well-known blockchains, such as Bitcoin and Ethereum [20] can largely be attributed to their decentralized nature and their capabilities to handle complex transactions with advanced cryptographic primitives. With currently a large market, blockchains have the potential to become a leading innovation in the finance and e-commerce sectors in the 21st century. Much existing blockchain infrastructure research and innovation focus on secure and efficient ways for participating nodes to maintain the public ledger (known as a layer-1 protocol). However, we note that fetching information from a well-maintained ledger is also a non-trivial issue. Ensuring that blockchains stay accessible to every user is essential if blockchains are to play a bigger role in everyday life—a public ledger is, by definition, only useful as long as people can interact with it. Given the recent growing public interest in blockchains, more users are interacting with blockchains every month, with as many as 875,000 transactions a day for popular blockchains such as Ethereum [20]. Trying to extract useful information from a flood of transactions requires powerful hardware for even a standard blockchain user who does not engage in profit-generating behavior (like mining), and it appears that the incentive mechanism in most blockchains is not equipped to deal with the issue. In most blockchain protocols, such as Bitcoin and Ethereum, participating nodes (miners in proof-of-work systems and validators in proof-of-stake systems) are incentivized to maintain the ledger by earning a small fee when proposing a new block to the ledger. While participating nodes in these blockchain protocols are incentivized to collect transactions and broadcast raw blocks to ensure their profit, they are not incentivized to publish refined information about the ledger they maintain. Consider these two examples: (1) A user wants to know how many coins there are in their Bitcoin wallet. (2) A user wants to know the current status of a smart contract they want to execute. Similar to these examples, most information users want to know is not directly related to the raw blocks that miners and validators publish. The users may entrust their assets fully to a third-party exchange and obtain information from the exchange, but the approach is significantly risky as evidenced by the recent FTX collpase [31]. Therefore, blockchain users need to devise a method to extract such information from blocks, either through some computation power that they own or by relying on a third-party service provider. In this paper, we compare the two current methods in practice that users adopt to obtain refined information from blockchains. One method involves running a full node locally. This method is usually capable of extracting much information from the blockchain without external reliance. In some cases though, additional indices are kept to ensure a faster query, such as Ethereum archive nodes and Solana RPC nodes. The other method is to rely on a third-service provider. We notice the trend that as the cost of running a full node grows, especially in Ethereum, many users are turning to third-party services, which carry their own security risks. We observe that running a full node and fully utilizing a trusted third-party service represent two extremes regarding blockchain accessibility: one with minimal reliance and maximal hardware requirement and one with maximal reliance and minimal hardware requirement. We also notice that when the required data on the blockchain is specific and limited, like when the users only care about one address that they own, specific wallet software is available to the users. While some of the wallet software queries an external node directly for data, others may download a portion of the blockchains and directly analyze it for the information the users care about. We categorize the software as specific light nodes. Meanwhile, we outline a recent trend in realizing a universal light node that can provide any information to users, not just one address [12], such as the one proposed by Ethereum [24]. Current research also includes so-called ultralight nodes, such as Flyclient [10], that step closer to relying on a third-party service that provides additional context for verification (also known as a prover in this context) than traditional light nodes that rely only on full nodes. Figure 1 shows a list of different methods to access blockchains. We think that amid many ways to access blockchains, it is still important to examine the basics of any web service: integrity, availability, and privacy. The blockchain itself is a technology of decentralization, yet too much reliance on a small number of third parties goes against this premise. Without a method to verify the correctness of data, integrity may be compromised if the said third parties provide incorrect data. With too much dependence on selected third parties to provide accessibility, availability may be impacted if they are unable or unwilling to provide service. Privacy is also a concern that needs addressing when querying any third party. We examine existing protocols in the market and find that many of them may be flawed in at least one of these aspects. Currently, the best way to access a blockchain while maintaining integrity, availability and privacy is still to run a full node locally. We consider it important to pay attention to these three aspects when designing any protocol to interact with blockchains to ensure functionality. This paper is available on arxiv under CC BY-NC-ND 4.0 DEED license. This paper is available on arxiv under CC BY-NC-ND 4.0 DEED license. available on arxiv

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