BARK

bark

ZURICH, Switzerland/20 August 2024/--ArkeFi announces Development of Fractional Ownership Protection (FOP) in Strategic Collaboration with The Barker Price. ArkeFi, the premier platform that tokenizes non-bankable assets (nBAs) such as art, cars, and collectibles, is excited to announce a strategic collaboration with The Barker Price to develop the groundbreaking Fractional Ownership Protection (FOP). This innovation will redefine security and accessibility for fractional investors in high-value assets. ArkeFi’s unique platform allows the sale of tokenized nBAs to fractional owners at 50% of their Fair Market Value (FMV). An essential feature of the platform is its smart contracts, which include an embedded option for sellers to repurchase their assets at a predetermined price, typically 55% of the FMV, within a certain timeframe. If this buy-back option is not exercised, the fractional owners assume full ownership of the asset, which can then be sold on the secondary market, resulting in significant upside potential. The Fractional Ownership Protection (FOP) being developed with The Barker Price will secure fractional owners' initial investments by covering 50% of the FMV and mitigating associated financial risks. By leveraging advanced AI, data analytics, and precise valuation techniques, FOP provides enhanced protection and accuracy in asset valuation. "We are thrilled to unveil the Fractional Ownership Protection (FOP) in collaboration with The Barker Price," said Patrick Schweiger, Co-Founder of ArkeFi. "We have closely observed how The Barker Price has developed a sophisticated, patented AI-valuation engine, complete with warranties for lenders of alternative assets. Integrating this cutting-edge technology into ArkeFi enables us to create a product never before seen in the crypto space. With FOP, we are significantly enhancing security and accessibility for fractional investors while offering unprecedented opportunities for substantial upside potential. This initiative underscores our commitment to innovation and advancing the crypto space." “We are excited to partner with ArkeFi on this groundbreaking FOP program. This initiative further enhances our commitment to providing innovative and secure financial solutions,” said Thomas Galbraith, CEO of The Barker Price. About ArkeFi: ArkeFi is pioneering the world's first peer-to-peer Fractional Option Financing platform for non-bankable assets (nBAs), supported by art collectors and owners of works by Pablo Picasso, Henri Matisse, Van Gogh, Zao Wou-ki, and Banksy. They are working with other nBAs such as cars (Ferrari 250 GT, McLaren Speedtail, Bugatti Chiron, Porsche 918, and more) and aim to expand to other nBA fields. The platform is now positioned as the Real World Asset Engine for Consumer Goods, facilitated by AI compute, to make these high-value assets more accessible and liquid – with support of the $RKFI utility token set to launch at the start of September 2024.You can visit the ArkeFi website here. About The Barker Price: Barker delivers mark-to-market valuations for alternative assets, backed by A-rated insurers, ensuring reliability and peace of mind. Valuations come with warranties that assure the accuracy of the prices. You can visit The Barker Price website here. Media Contact: ArkeFi: Bankole Fadimiluyi, bf@arkefi.com The Barker Price: Paulina Amato, paulina@thebarkerprice.com This story was distributed as a release by Btcwire under HackerNoon’s Business Blogging Program. Learn more about the program here. ZURICH, Switzerland/20 August 2024/--ArkeFi announces Development of Fractional Ownership Protection (FOP) in Strategic Collaboration with The Barker Price. ArkeFi, the premier platform that tokenizes non-bankable assets (nBAs) such as art, cars, and collectibles, is excited to announce a strategic collaboration with The Barker Price to develop the groundbreaking Fractional Ownership Protection (FOP). This innovation will redefine security and accessibility for fractional investors in high-value assets. ArkeFi’s unique platform allows the sale of tokenized nBAs to fractional owners at 50% of their Fair Market Value (FMV). An essential feature of the platform is its smart contracts, which include an embedded option for sellers to repurchase their assets at a predetermined price, typically 55% of the FMV, within a certain timeframe. If this buy-back option is not exercised, the fractional owners assume full ownership of the asset, which can then be sold on the secondary market, resulting in significant upside potential. The Fractional Ownership Protection (FOP) being developed with The Barker Price will secure fractional owners' initial investments by covering 50% of the FMV and mitigating associated financial risks. By leveraging advanced AI, data analytics, and precise valuation techniques, FOP provides enhanced protection and accuracy in asset valuation. "We are thrilled to unveil the Fractional Ownership Protection (FOP) in collaboration with The Barker Price," said Patrick Schweiger, Co-Founder of ArkeFi. "We are thrilled to unveil the Fractional Ownership Protection (FOP) in collaboration with The Barker Price," said Patrick Schweiger, Co-Founder of ArkeFi. "We have closely observed how The Barker Price has developed a sophisticated, patented AI-valuation engine, complete with warranties for lenders of alternative assets. Integrating this cutting-edge technology into ArkeFi enables us to create a product never before seen in the crypto space. With FOP, we are significantly enhancing security and accessibility for fractional investors while offering unprecedented opportunities for substantial upside potential. This initiative underscores our commitment to innovation and advancing the crypto space." "We have closely observed how The Barker Price has developed a sophisticated, patented AI-valuation engine, complete with warranties for lenders of alternative assets. Integrating this cutting-edge technology into ArkeFi enables us to create a product never before seen in the crypto space. With FOP, we are significantly enhancing security and accessibility for fractional investors while offering unprecedented opportunities for substantial upside potential. This initiative underscores our commitment to innovation and advancing the crypto space." “We are excited to partner with ArkeFi on this groundbreaking FOP program. This initiative further enhances our commitment to providing innovative and secure financial solutions,” said Thomas Galbraith, CEO of The Barker Price. “We are excited to partner with ArkeFi on this groundbreaking FOP program. This initiative further enhances our commitment to providing innovative and secure financial solutions,” said Thomas Galbraith, CEO of The Barker Price. About ArkeFi: ArkeFi is pioneering the world's first peer-to-peer Fractional Option Financing platform for non-bankable assets (nBAs), supported by art collectors and owners of works by Pablo Picasso, Henri Matisse, Van Gogh, Zao Wou-ki, and Banksy. They are working with other nBAs such as cars (Ferrari 250 GT, McLaren Speedtail, Bugatti Chiron, Porsche 918, and more) and aim to expand to other nBA fields. The platform is now positioned as the Real World Asset Engine for Consumer Goods, facilitated by AI compute, to make these high-value assets more accessible and liquid – with support of the $RKFI utility token set to launch at the start of September 2024.You can visit the ArkeFi website here. About The Barker Price: Barker delivers mark-to-market valuations for alternative assets, backed by A-rated insurers, ensuring reliability and peace of mind. Valuations come with warranties that assure the accuracy of the prices. You can visit The Barker Price website here. Media Contact: ArkeFi: Bankole Fadimiluyi, bf@arkefi.com The Barker Price: Paulina Amato, paulina@thebarkerprice.com This story was distributed as a release by Btcwire under HackerNoon’s Business Blogging Program. Learn more about the program here. This story was distributed as a release by Btcwire under HackerNoon’s Business Blogging Program. Learn more about the program here . here

ArkeFi And The Barker Price Announce Strategic Collaboration For Fractional Ownership Protection

ArkeFi এবং বার্কার প্রাইস ভগ্নাংশের মালিকানা সুরক্ষার জন্য কৌশলগত সহযোগিতা ঘোষণা করেছে

ArkeFi und The Barker Price geben strategische Zusammenarbeit zum Schutz von Teileigentum bekannt

ArkeFi y The Barker Price anuncian una colaboración estratégica para la protección de la propiedad fraccionada

ArkeFi et The Barker Price annoncent une collaboration stratégique pour la protection de la propriété fractionnée

आर्केफाई और द बार्कर प्राइस ने आंशिक स्वामित्व संरक्षण के लिए रणनीतिक सहयोग की घोषणा की

ArkeFiとBarker Priceが分割所有権保護のための戦略的提携を発表

ArkeFi와 Barker Price, 분할 소유권 보호를 위한 전략적 협력 발표

ArkeFi e The Barker Price anunciam colaboração estratégica para proteção de propriedade fracionada

ArkeFi и The Barker Price объявляют о стратегическом сотрудничестве для защиты долевой собственности

ArkeFi ve Barker Price, Kesirli Sahiplik Koruması İçin Stratejik İşbirliği Duyurdu

ArkeFi và Barker Price công bố hợp tác chiến lược để bảo vệ quyền sở hữu một phần

ArkeFi 与 Barker Price 宣布就部分所有权保护达成战略合作

After my latest post about how to build your own RAG and run it locally, today, we're taking it a step further by not only implementing the conversational abilities of large language models but also adding listening and speaking capabilities. The idea is straightforward: we are going to create a voice assistant reminiscent of Jarvis or Friday from the iconic Iron Man movies, which can operate offline on your computer. Since this is an introductory tutorial, I will implement it in Python and keep it simple enough for beginners. Lastly, I will provide some guidance on how to scale the application. Techstack First, you should set up a virtual Python environment. You have several options for this, including pyenv, virtualenv, poetry, and others that serve a similar purpose. Personally, I'll use Poetry for this tutorial due to my personal preferences. Here are several crucial libraries you'll need to install: : For a visually appealing console output. rich : A robust tool for speech-to-text conversion. openai-whisper : A cutting-edge library for text-to-speech synthesis, ensuring high-quality audio output. suno-bark : A straightforward library for interfacing with Large Language Models (LLMs). langchain , , and : Essential for audio recording and playback. sounddevice pyaudio speechrecognition For a detailed list of dependencies, refer to the link . here The most critical component here is the Large Language Model (LLM) backend, for which we will use Ollama. is widely recognized as a popular tool for running and serving LLMs offline. If Ollama is new to you, I recommend checking out my previous article on offline RAG: Basically, you just need to download the Ollama application, pull your preferred model, and run it. Ollama "Build Your Own RAG and Run It Locally: Langchain + Ollama + Streamlit." Architecture Okay, if everything has been set up, let's proceed to the next step. Below is the overall architecture of our application, which fundamentally comprises 3 main components: : Utilizing , we convert spoken language into text. Whisper's training on diverse datasets ensures its proficiency across various languages and dialects. Speech Recognition OpenAI's Whisper : For the conversational capabilities, we'll employ the Langchain interface for the model, which is served using Ollama. This setup promises a seamless and engaging conversational flow. Conversational Chain Llama-2 : The transformation of text to speech is achieved through , a state-of-the-art model from Suno AI, renowned for its lifelike speech production. Speech Synthesizer Bark The workflow is straightforward: record speech, transcribe to text, generate a response using an LLM, and vocalize the response using Bark. Sequence diagram for voice assistant with Whisper, Ollama, and Bark. Implementation The implementation begins with crafting a based on Bark, incorporating methods for synthesizing speech from text and handling longer text inputs seamlessly as follows: TextToSpeechService import nltk
import torch
import warnings
import numpy as np
from transformers import AutoProcessor, BarkModel

warnings.filterwarnings(
    "ignore",
    message="torch.nn.utils.weight_norm is deprecated in favor of torch.nn.utils.parametrizations.weight_norm.",
)


class TextToSpeechService:
    def __init__(self, device: str = "cuda" if torch.cuda.is_available() else "cpu"):
        """
        Initializes the TextToSpeechService class.
        Args:
            device (str, optional): The device to be used for the model, either "cuda" if a GPU is available or "cpu".
            Defaults to "cuda" if available, otherwise "cpu".
        """
        self.device = device
        self.processor = AutoProcessor.from_pretrained("suno/bark-small")
        self.model = BarkModel.from_pretrained("suno/bark-small")
        self.model.to(self.device)

    def synthesize(self, text: str, voice_preset: str = "v2/en_speaker_1"):
        """
        Synthesizes audio from the given text using the specified voice preset.
        Args:
            text (str): The input text to be synthesized.
            voice_preset (str, optional): The voice preset to be used for the synthesis. Defaults to "v2/en_speaker_1".
        Returns:
            tuple: A tuple containing the sample rate and the generated audio array.
        """
        inputs = self.processor(text, voice_preset=voice_preset, return_tensors="pt")
        inputs = {k: v.to(self.device) for k, v in inputs.items()}

        with torch.no_grad():
            audio_array = self.model.generate(**inputs, pad_token_id=10000)

        audio_array = audio_array.cpu().numpy().squeeze()
        sample_rate = self.model.generation_config.sample_rate
        return sample_rate, audio_array

    def long_form_synthesize(self, text: str, voice_preset: str = "v2/en_speaker_1"):
        """
        Synthesizes audio from the given long-form text using the specified voice preset.
        Args:
            text (str): The input text to be synthesized.
            voice_preset (str, optional): The voice preset to be used for the synthesis. Defaults to "v2/en_speaker_1".
        Returns:
            tuple: A tuple containing the sample rate and the generated audio array.
        """
        pieces = []
        sentences = nltk.sent_tokenize(text)
        silence = np.zeros(int(0.25 * self.model.generation_config.sample_rate))

        for sent in sentences:
            sample_rate, audio_array = self.synthesize(sent, voice_preset)
            pieces += [audio_array, silence.copy()]

        return self.model.generation_config.sample_rate, np.concatenate(pieces) : The class takes an optional parameter, which specifies the device to be used for the model (either if a GPU is available, or ). It loads the Bark model and the corresponding processor from the pre-trained model. You can also use the large version by specifying for the model loader. Initialization ( __init__ ) device cuda cpu suno/bark-small suno/bark : This method takes a input and a parameter, which specifies the voice to be used for the synthesis. You can check out other value . It uses the to prepare the input text and the voice preset, and then generates the audio array using the method. The generated audio array is converted to a NumPy array and the sample rate is returned along with the audio array. Synthesize ( synthesize ) text voice_preset voice_preset here processor model.generate() : This method is used for synthesizing longer text inputs. It first tokenizes the input text into sentences using the function. For each sentence, it calls the method to generate the audio array. It then concatenates the generated audio arrays, with a short silence (0.25 seconds) added between each sentence. Long-form Synthesize ( long_form_synthesize ) nltk.sent_tokenize synthesize Now that we have the set up, we need to prepare the Ollama server for the large language model (LLM) serving. To do this, you'll need to follow these steps: TextToSpeechService : Run the following command to download the latest Llama-2 model from the Ollama repository: Pull the latest Llama-2 model ollama pull llama2 . : If the server is not yet started, execute the following command to start it: . Start the Ollama server ollama serve Once you've completed these steps, your application will be able to use the Ollama server and the Llama-2 model to generate responses to user input. Next, we'll move to the main application logic. First, we need to initialize the following components: : We'll use the Rich library to create a better interactive console for the user within the terminal. Rich Console : We'll initialize a Whisper speech recognition model which is a state-of-the-art open-source speech recognition system developed by OpenAI. We'll use the base English model ( ) for transcribing user input. Whisper Speech-to-Text base.en : We'll initialize a Bark text-to-speech synthesizer instance, which was implemented above. Bark Text-to-Speech : We'll use the built-in from the Langchain library which provides a template for managing the conversational flow. We'll configure it to use the Llama-2 language model with the Ollama backend. Conversational Chain ConversationalChain import time
import threading
import numpy as np
import whisper
import sounddevice as sd
from queue import Queue
from rich.console import Console
from langchain.memory import ConversationBufferMemory
from langchain.chains import ConversationChain
from langchain.prompts import PromptTemplate
from langchain_community.llms import Ollama
from tts import TextToSpeechService

console = Console()
stt = whisper.load_model("base.en")
tts = TextToSpeechService()

template = """
You are a helpful and friendly AI assistant. You are polite, respectful, and aim to provide concise responses of less 
than 20 words.
The conversation transcript is as follows:
{history}
And here is the user's follow-up: {input}
Your response:
"""
PROMPT = PromptTemplate(input_variables=["history", "input"], template=template)
chain = ConversationChain(
    prompt=PROMPT,
    verbose=False,
    memory=ConversationBufferMemory(ai_prefix="Assistant:"),
    llm=Ollama(),
) Now, let's define the necessary functions: : This function runs in a separate thread to capture audio data from the user's microphone using the . The callback function is called whenever new audio data is available, and it puts the data into a for further processing. record_audio sounddevice.RawInputStream data_queue : This function utilizes the Whisper instance to transcribe the audio data from the into text. transcribe data_queue : This function feeds the current conversation context to the Llama-2 language model (via the Langchain ) and retrieves the generated text response. get_llm_response ConversationalChain : This function takes the audio waveform generated by the Bark text-to-speech engine and plays it back to the user using a sound playback library (e.g., ). play_audio sounddevice def record_audio(stop_event, data_queue):
    """
    Captures audio data from the user's microphone and adds it to a queue for further processing.
    Args:
        stop_event (threading.Event): An event that, when set, signals the function to stop recording.
        data_queue (queue.Queue): A queue to which the recorded audio data will be added.
    Returns:
        None
    """
    def callback(indata, frames, time, status):
        if status:
            console.print(status)
        data_queue.put(bytes(indata))

    with sd.RawInputStream(
        samplerate=16000, dtype="int16", channels=1, callback=callback
    ):
        while not stop_event.is_set():
            time.sleep(0.1)

def transcribe(audio_np: np.ndarray) -> str:
    """
    Transcribes the given audio data using the Whisper speech recognition model.
    Args:
        audio_np (numpy.ndarray): The audio data to be transcribed.
    Returns:
        str: The transcribed text.
    """
    result = stt.transcribe(audio_np, fp16=False)  # Set fp16=True if using a GPU
    text = result["text"].strip()
    return text

def get_llm_response(text: str) -> str:
    """
    Generates a response to the given text using the Llama-2 language model.
    Args:
        text (str): The input text to be processed.
    Returns:
        str: The generated response.
    """
    response = chain.predict(input=text)
    if response.startswith("Assistant:"):
        response = response[len("Assistant:") :].strip()
    return response

def play_audio(sample_rate, audio_array):
    """
    Plays the given audio data using the sounddevice library.
    Args:
        sample_rate (int): The sample rate of the audio data.
        audio_array (numpy.ndarray): The audio data to be played.
    Returns:
        None
    """
    sd.play(audio_array, sample_rate)
    sd.wait() Then, we define the main application loop. The main application loop guides the user through the conversational interaction as follows: The user is prompted to press Enter to start recording their input. Once the user presses Enter, the function is called in a separate thread to capture the user's audio input. record_audio When the user presses Enter again to stop the recording, the audio data is transcribed using the function. transcribe The transcribed text is then passed to the function, which generates a response using the Llama-2 language model. get_llm_response The generated response is printed to the console and played back to the user using the function. play_audio if __name__ == "__main__":
    console.print("[cyan]Assistant started! Press Ctrl+C to exit.")

    try:
        while True:
            console.input(
                "Press Enter to start recording, then press Enter again to stop."
            )

            data_queue = Queue()  # type: ignore[var-annotated]
            stop_event = threading.Event()
            recording_thread = threading.Thread(
                target=record_audio,
                args=(stop_event, data_queue),
            )
            recording_thread.start()

            input()
            stop_event.set()
            recording_thread.join()

            audio_data = b"".join(list(data_queue.queue))
            audio_np = (
                np.frombuffer(audio_data, dtype=np.int16).astype(np.float32) / 32768.0
            )

            if audio_np.size > 0:
                with console.status("Transcribing...", spinner="earth"):
                    text = transcribe(audio_np)
                console.print(f"[yellow]You: {text}")

                with console.status("Generating response...", spinner="earth"):
                    response = get_llm_response(text)
                    sample_rate, audio_array = tts.long_form_synthesize(response)

                console.print(f"[cyan]Assistant: {response}")
                play_audio(sample_rate, audio_array)
            else:
                console.print(
                    "[red]No audio recorded. Please ensure your microphone is working."
                )

    except KeyboardInterrupt:
        console.print("\n[red]Exiting...")

    console.print("[blue]Session ended.") Result Once everything is put down together, we can run the application as shown in the video above. The application runs quite slowly on my MacBook because the Bark model is large, even in its smaller version. Therefore, I have slightly sped up the video. For those with a CUDA-enabled computer, it might run faster. Here are the key features of our application: : Users can start and stop recording their voice input, and the assistant responds by playing back the generated audio. Voice-based interaction The assistant maintains the context of the conversation, enabling more coherent and relevant responses. The use of the Llama-2 language model allows the assistant to provide concise and focused responses. Conversational context: For those aiming to elevate this application to a production-ready status, the following enhancements are recommended: : Incorporate optimized versions of the models, such as whisper.cpp, llama.cpp, and bark.cpp, which are designed to boost performance, especially on lower-end computers. Performance Optimization : Implement a system that allows users to customize the bot's persona and prompt, enabling the creation of different types of assistants (e.g., personal, professional, or domain-specific). Customizable Bot Prompts : Develop a user-friendly GUI to enhance the overall user experience, making the application more accessible and visually appealing. Graphical User Interface (GUI) : Expand the application to support multimodal interactions, such as the ability to generate and display images, diagrams, or other visual content in addition to the voice-based responses. Multimodal Capabilities Finally, we have completed our simple voice assistant application, full code can be found at: . This combination of speech recognition, language modeling, and text-to-speech technologies demonstrates how we can build something that sounds difficult but can actually run on your computer. Let's enjoy coding, and don't forget to subscribe to so you don't miss the latest in AI and programming articles. https://github.com/vndee/local-talking-llm my blog Also published here

How to Build Your Own Voice Assistant and Run it Locally Using Whisper + Ollama + Bark

কীভাবে আপনার নিজের ভয়েস সহকারী তৈরি করবেন এবং হুইস্পার + ওল্লামা + বার্ক ব্যবহার করে স্থানীয়ভাবে এটি চালাবেন

So erstellen Sie Ihren eigenen Sprachassistenten und führen ihn lokal mit Whisper + Ollama + Bark aus

Cómo crear su propio asistente de voz y ejecutarlo localmente usando Whisper + Ollama + Bark

Comment créer votre propre assistant vocal et l'exécuter localement à l'aide de Whisper + Ollama + Bark

अपना खुद का वॉयस असिस्टेंट कैसे बनाएं और इसे व्हिस्पर + ओलामा + बार्क का उपयोग करके स्थानीय रूप से कैसे चलाएं

独自の音声アシスタントを構築し、Whisper + Ollama + Bark を使用してローカルで実行する方法

나만의 음성 어시스턴트를 구축하고 Whisper + Ollama + Bark를 사용하여 로컬에서 실행하는 방법

Como construir seu próprio assistente de voz e executá-lo localmente usando Whisper + Ollama + Bark

Как создать собственный голосовой помощник и запустить его локально с помощью Whisper + Ollama + Bark

Kendi Sesli Asistanınızı Oluşturma ve Whisper + Ollama + Bark Kullanarak Yerel Olarak Çalıştırma

Cách xây dựng trợ lý giọng nói của riêng bạn và chạy nó cục bộ bằng Whisper + Ollama + Bark

如何构建您自己的语音助手并使用 Whisper + Ollama + Bark 在本地运行

Abandoned by Jules Verne, is part of the HackerNoon Books Series. You can jump to any chapter in this book . CHAPTER II here CHAPTER II First Trial of the Canoe—A Wreck on the Coast—Towing—Flotsam Point—Inventory of the Case: Tools, Weapons, Instruments, Clothes, Books, Utensils—What Pencroft misses—The Gospel—A Verse from the Sacred Book. On the 9th of October the bark canoe was entirely finished. Pencroft had kept his promise, and a light boat, the shell of which was joined together by the flexible twigs of the crejimba, had been constructed in five days. A seat in the stern, a second seat in the middle to preserve the equilibrium, a third seat in the bows, rowlocks for the two oars, a scull to steer with, completed the little craft, which was twelve feet long, and did not weigh more than 200 pounds. The operation of launching it was extremely simple. The canoe was carried to the beach and laid on the sand before Granite House, and the rising tide floated it. Pencroft, who leapt in directly, manœuvred it with the scull and declared it to be just the thing for the purpose to which they wished to put it. "Hurrah!" cried the sailor, who did not disdain to celebrate thus his own triumph. "With this we could go round—" "The world?" asked Gideon Spilett. "No, the island. Some stones for ballast, a mast, and a sail, which the captain will make for us some day, and we shall go splendidly! Well, captain—and you, Mr. Spilett; and you, Herbert; and you, Neb—aren't you coming to try our new vessel? Come along! we must see if it will carry all five of us!" This was certainly a trial which ought to be made. Pencroft soon brought the canoe to the shore by a narrow passage among the rocks, and it was agreed that they should make a trial of the boat that day by following the shore as far as the first point at which the rocks of the south ended. As they embarked, Neb cried,— "But your boat leaks rather, Pencroft." "That's nothing, Neb," replied the sailor; "the wood will get seasoned. In two days there won't be a single leak, and our boat will have no more water in her than there is in the stomach of a drunkard. Jump in!" They were soon all seated, and Pencroft shoved off. The weather was magnificent, the sea as calm as if its waters were contained within the narrow limits of a lake. Thus the boat could proceed with as much security as if it was ascending the tranquil current of the Mercy. Neb took one of the oars, Herbert the other, and Pencroft remained in the stern in order to use the skull. The sailor first crossed the channel, and steered close to the southern point of the islet. A light breeze blew from the south. No roughness was found either in the channel or the green sea. A long swell, which the canoe scarcely felt, as it was heavily laden, rolled regularly over the surface of the water. They pulled out about half a mile distant from the shore, that they might have a good view of Mount Franklin. Pencroft afterwards returned towards the mouth of the river. The boat then skirted the shore, which, extending to the extreme point, hid all Tadorn's Fens. This point, of which the distance was increased by the irregularity of the coast, was nearly three miles from the Mercy. The settlers resolved to go to its extremity, and only go beyond it as much as was necessary to take a rapid survey of the coast as far as Claw Cape. The canoe followed the windings of the shore, avoiding the rocks which fringed it, and which the rising tide began to cover. The cliff gradually sloped away from the mouth of the river to the point. This was formed of granite rocks, capriciously distributed, very different from the cliff at Prospect Heights, and of an extremely wild aspect. It might have been said that an immense cartload of rocks had been emptied out there. There was no vegetation on this sharp promontory, which projected two miles from the forest, and it thus represented a giant's arm stretched out from a leafy sleeve. The canoe, impelled by the two oars, advanced without difficulty. Gideon Spilett, pencil in one hand and note-book in the other, sketched the coast in bold strokes. Neb, Herbert, and Pencroft chatted, whilst examining this part of their domain, which was new to them, and, in proportion as the canoe proceeded towards the south, the two Mandible Capes appeared to move, and surround Union Bay more closely. As to Cyrus Harding, he did not speak; he simply gazed, and by the mistrust which his look expressed, it appeared that he was examining some strange country. In the meanwhile, after a voyage of three quarters of an hour, the canoe reached the extremity of the point, and Pencroft was preparing to return, when Herbert, rising, pointed to a black object, saying,— "What do I see down there on the beach?" All eyes turned towards the point indicated. "Why," said the reporter, "there is something. It looks like part of a wreck half buried in the sand." "Ah!" cried Pencroft, "I see what it is!" "What?" asked Neb. "Barrels, barrels, which perhaps are full," replied the sailor. "Pull to the shore, Pencroft!" said Cyrus. A few strokes of the oar brought the canoe into a little creek, and its passengers leapt on shore. Pencroft was not mistaken. Two barrels were there, half buried in the sand, but still firmly attached to a large chest, which, sustained by them, had floated to the moment when it stranded on the beach. "There has been a wreck, then, in some part of the island," said Herbert. "Evidently," replied Spilett. "But what's in this chest?" cried Pencroft, with very natural impatience. "What's in this chest? It is shut up, and nothing to open it with! Well, perhaps a stone—" And the sailor, raising a heavy block, was about to break in one of the sides of the chest, when the engineer arrested his hand. "Pencroft," said he, "can you restrain your impatience for one hour only?" "But, captain, just think! Perhaps there is everything we want in there!" "We shall find that out, Pencroft," replied the engineer; "but trust to me, and do not break the chest, which may be useful to us. We must convey it to Granite House, where we can open it easily and without breaking it. It is quite prepared for a voyage, and, since it has floated here, it may just as well float to the mouth of the river." "You are right, captain, and I was wrong, as usual," replied the sailor. The engineer's advice was good. In fact, the canoe probably would not have been able to contain the articles possibly enclosed in the chest, which doubtless was heavy, since two empty barrels were required to buoy it up. It was, therefore, much better to tow it to the beach at Granite House. And now, whence had this chest come? That was the important question Cyrus Harding and his companions looked attentively around them, and examined the shore for several hundred steps. No other articles or pieces of wreck could be found. Herbert and Neb climbed a high rock to survey the sea, but there was nothing in sight—neither a dismasted vessel nor a ship under sail. However, there was no doubt that there had been a wreck Perhaps this incident was connected with that of the bullet? Perhaps strangers had landed on another part of the island? Perhaps they were still there? But the thought which came naturally to the settlers was, that these strangers could not be Malay pirates, for the chest was evidently of American or European make. All the party returned to the chest, which was of an unusually large size. It was made of oak wood, very carefully closed and covered with a thick hide, which was secured by copper nails. The two great barrels, hermetically sealed, but which sounded hollow and empty, were fastened to its sides by strong ropes knotted with a skill which Pencroft directly pronounced sailors alone could exhibit. It appeared to be in a perfect state of preservation, which was explained by the fact that it had stranded on a sandy beach, and not among rocks. They had no doubt whatever, on examining it carefully, that it had not been long in the water, and that its arrival on this coast was recent. The water did not appear to have penetrated to the inside, and the articles which it contained were no doubt uninjured. It was evident that this chest had been thrown overboard from some dismasted vessel driven towards the island, and that, in the hope that it would reach the land, where they might afterwards find it, the passengers had taken the precaution to buoy it up by means of this floating apparatus. "We will tow this chest to Granite House," said the engineer, "where we can make an inventory of its contents, then, if we discover any of the survivors from the supposed wreck, we can return it to those to whom it belongs. If we find no one—" "We will keep it for ourselves!" cried Pencroft "But what in the world can there be in it?" The sea was already approaching the chest, and the high tide would evidently float it. One of the ropes which fastened the barrels was partly unlashed and used as a cable to unite the floating apparatus with the canoe. Pencroft and Neb then dug away the sand with their oars, so as to facilitate the moving of the chest, towing which the boat soon began to double the point to which the name of Flotsam Point was given. The chest was heavy, and the barrels were scarcely sufficient to keep it above water. The sailor also feared every instant that it would get loose and sink to the bottom of the sea. But happily his fears were not realised, and an hour and a half after they set out—all that time had been taken up in going a distance of three miles—the boat touched the beach below Granite House. Canoe and chest were then hauled up on the sand, and as the tide was then going out, they were soon left high and dry. Neb, hurrying home, brought back some tools with which to open the chest in such a way that it might be injured as little as possible, and they proceeded to its inventory. Pencroft did not try to hide that he was greatly excited. The sailor began by detaching the two barrels, which, being in good condition, would of course be of use. Then the locks were forced with a cold chisel and hammer, and the lid thrown back. A second casing of zinc lined the interior of the chest, which had been evidently arranged that the articles which it enclosed might under any circumstances be sheltered from damp. "Oh!" cried Neb, "suppose it's jam!". "I hope not," replied the reporter. "If only there was—" said the sailor in a low voice. "What?" asked Neb, who overheard him. "Nothing!" The covering of zinc was torn off and thrown back over the sides of the chest, and by degrees numerous articles of very varied character were produced and strewn about on the sand. At each new object Pencroft uttered fresh hurrahs, Herbert clapped his hands, and Neb danced—like a nigger. There were books which made Herbert wild with joy, and cooking utensils which Neb covered with kisses! In short, the colonists had reason to be extremely satisfied, for this chest contained tools, weapons, instruments, clothes, books; and this is the exact list of them as stated in Gideon Spilett's note-book:— Tools:—3 knives with several blades, 2 woodmen's axes, 2 carpenter's hatchets, 3 planes, 2 adzes, 1 twibil or mattock, 6 chisels, 2 files, 3 hammers, 3 gimlets, 2 augers, 10 bags of nails and screws, 3 saws of different sizes, 2 boxes of needles. Weapons:—2 flint-lock guns, 2 for percussion caps, 2 breech-loader carbines, 5 boarding cutlasses, 4 sabres, 2 barrels of powder, each containing twenty-five pounds; 12 boxes of percussion caps. Instruments:—1 sextant, 1 double opera-glass, 1 telescope, 1 box of mathematical instruments, 1 mariner's compass, 1 Fahrenheit thermometer, 1 aneroid barometer, 1 box containing a photographic apparatus, object-glass, plates, chemicals, etc. Clothes:—2 dozen shirts of a peculiar material resembling wool, but evidently of a vegetable origin; 3 dozen stockings of the same material. Utensils:—1 iron pot, 6 copper saucepans, 3 iron dishes, 10 metal plates, 2 kettles, 1 portable stove, 6 table-knives. Books:—1 Bible, 1 atlas, 1 dictionary of the different Polynesian idioms, 1 dictionary of natural science, in six volumes; 3 reams of white paper, 2 books with blank pages. "It must be allowed," said the reporter, after the inventory had been made, "that the owner of this chest was a practical man! Tools, weapons, instruments, clothes, utensils, books—nothing is wanting! It might really be said that he expected to be wrecked, and had prepared for it beforehand." "Nothing is wanting, indeed," murmured Cyrus Harding thoughtfully. "And for a certainty," added Herbert, "the vessel which carried this chest and its owner was not a Malay pirate!" "Unless," said Pencroft, "the owner had been taken prisoner by pirates—" "That is not admissible," replied the reporter. "It is more probable that an American or European vessel has been driven into this quarter, and that her passengers, wishing to save necessaries at least, prepared this chest and threw it overboard." "Is that your opinion, captain?" asked Herbert. "Yes, my boy," replied the engineer, "that may have been the case. It is possible that at the moment, or in expectation of a wreck, they collected into this chest different articles of the greatest use in hopes of finding it again on the coast—" "Even the photographic box!" exclaimed the sailor incredulously. "As to that apparatus," replied Harding, "I do not quite see the use of it; and a more complete supply of clothes or more abundant ammunition would have been more valuable to us as well as to any other castaways!" "But isn't there any mark or direction on these instruments, tools, or books, which would tell us something about them?" asked Gideon Spilett. That might be ascertained. Each article was carefully examined, especially the books, instruments and weapons. Neither the weapons nor the instruments, contrary to the usual custom, bore the name of the maker; they were, besides, in a perfect state, and did not appear to have been used. The same peculiarity marked the tools and utensils; all were new, which proved that the articles had not been taken by chance and thrown into the chest, but, on the contrary, that the choice of the things had been well considered and arranged with care. This was also indicated by a second case of metal which had preserved them from damp, and which could not have been soldered in a moment of haste. As to the dictionaries of natural science and Polynesian idioms, both were English, but they neither bore the name of the publisher nor the date of publication. The same with the Bible printed in English, in quarto, remarkable in a typographical point of view, and which appeared to have been often used. The atlas was a magnificent work, comprising maps of every country in the world, and several planispheres arranged upon Mercator's projection, aid of which the nomenclature was in French—but which also bore neither date nor name of publisher. There was nothing, therefore, on these different articles by which they could be traced and nothing consequently of a nature to show the nationality of the vessel which must have recently passed these shores. But, wherever the chest might have come from, it was a treasure to the settlers on Lincoln Island. Till then, by making use of the productions of nature, they had created everything for themselves, and, thanks to their intelligence, they had managed without difficulty. But did it not appear as if Providence had wished to reward them by sending them these productions of human industry? Their thanks rose unanimously to Heaven. However, one of them was not quite satisfied: it was Pencroft. It appeared that the chest did not contain some thing which he evidently held in great esteem, for in proportion as they approached the bottom of the box, his hurrahs diminished in heartiness, and, the inventory finished, he was heard to mutter these words— "That's all very fine, but you can see that there is nothing for me in that box!" This led Neb to say,— "Why, friend Pencroft, what more do you expect?" "Half a pound of tobacco," replied Pencroft seriously, "and nothing would have been wanting to complete my happiness." No one could help laughing at this speech of the sailor's. But the result of this discovery of the chest was, that it was more than ever necessary to explore the island thoroughly. It was therefore agreed that the next morning at break of day they should set out, by ascending the Mercy so as to reach the western shore. If any castaways had landed on the coast, it was to be feared they were without resources, and it was therefore the more necessary to carry help to them without delay. During the day the different articles were carried to Granite House, where they were methodically arranged in the great hall. This day—the 29th of October—happened to be a Sunday, and, before going to bed, Herbert asked the engineer if he would not read them something from the Gospel. "Willingly," replied Cyrus Harding. He took the sacred volume, and was about to open it, when Pencroft stopped him, saying,— "Captain, I am superstitious. Open at random and read the first verse which your eye falls upon. We will see if it applies to our situation." Cyrus Harding smiled at the sailor's idea, and, yielding to his wish, he opened exactly at a place where the leaves were separated by a marker. Immediately his eyes were attracted by a cross which, made with a pencil, was placed against the eighth verse of the seventh chapter of the Gospel of St. Matthew. He read the verse, which was this:— "For every one that asketh receiveth; and he that seeketh findeth." 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. Jules Verne (2010). Abandoned. Urbana, Illinois: Project Gutenberg. Retrieved October 2022 https://www.gutenberg.org/cache/epub/33516/pg33516-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 , located at . www.gutenberg.org https://www.gutenberg.org/policy/license.html

On the 9th of October the bark canoe was entirely finished

Realistic Text-to-Speech Voice Synthesis: Comparing Tortoise and Bark

Hello, loyal readers! After republishing my first Women in Information series from last fall, I’m now ready to republish my second series from this spring. These interviews have proven to be really popular, and I’m honoured to bring them to Hacker Noon. Security I will do a third series for Fall 2017. If you’re a woman or non-male who works in , or you know someone who is, cybersecurity feel free to tweet me about it! I have who help to encourage my unpaid writing. Most of my writing for corporate blogs, and my writing for Peerlyst is paid, but this isn’t. If you enjoy pieces like this, my Patreon support helps make it possible. , even for only a couple of bucks per month, and I’ll greatly appreciate it. six Patreon supporters Consider becoming a patron This was originally published on Tripwire’s State of Security blog in April. My of interviews on women (and non-males) in information security was really popular. I spoke to some amazing minds in the cybersecurity field last fall. As spring arrived, I figured that there are probably a lot more professionals in our field who also have interesting stories to tell. last series Encouraging more non-males to enter the industry will inevitably benefit cybersecurity as a whole. In resuming my series, hopefully more readers will be inspired. This time, I spoke to . She owns , for which she blogs about news and ideas regarding the human element of cybersecurity. Human beings are the greatest vulnerability, after all! Since 2013, she has run her own firm, J L Barker Ltd., and she recently co-founded Redacted Firm. She is engaged by organisations of all sizes, from multi-national firms to SMEs. She has also appeared at important security events, such as and . Dr. Jessica Barker Cyber.uk SteelCon 2016 Infosecurity Europe 2016 So you run Cyber.uk. What compelled you to start that venture? Kim Crawley: I wanted a place to write accessible articles on cybersecurity that people of any level of knowledge or understanding could hopefully engage with and get something from if they are interested in the subject. I do research from time to time, where I generally look at attitudes and behaviours online. For example, I surveyed 1,000 people in the UK about their attitudes towards biometrics replacing passwords; 1,000 people about whether they know of 2FA; and 3,000 people in the UK, US and Germany about their opinions of Edward Snowden’s actions. Dr. Jessica Barker: I think that’s a great motive. Ignorance of cybersecurity is harming laypeople, and they need knowledge. KC: I totally agree. I think there is an onus on us in the cybersecurity profession to communicate more effectively about our work, the threats online, and what people and organizations can do to better protect themselves. JB: I try to write most of my articles with technical laypeople in mind. But when my non-IT friends read my articles, they say that they’re still difficult to understand. Educating end users can be a challenge. I really appreciate how you recognize human beings as the most significant vulnerabilty. KC: We all get used to the language of our profession and can become detached from the level of understanding that most people have when it comes to the internet, security and privacy. JB: Yes, I think you’re exactly correct. A lot of laypeople don’t even know the word “malware.” KC: You’re absolutely right about malware. I was on a pretty popular radio show in the UK (the on BBC Radio 2) talking about ransomware. Even with my perspective and determination to keep in touch with what the average person knows about security, I was shocked at how low awareness of ransomware is. We all know in the industry that it’s one of the biggest threats at the moment and has been that way for a while. But most people haven’t heard of it. JB: Jeremy Vine Show That’s incredible considering that I’ve seen ransomware in Windows clients since a decade ago. I had to deal with consumers freaking out about it. KC: I think the greatest misconception laypeople have about “hacking” is that they believe how it’s depicted in Hollywood. A “hacker” typing commands into a terminal at 300 words per minute overlooks the fact that social engineering is such a major attack method. Yes, I agree. I work with organizations on social engineering awareness, and it’s interesting to see how shocked people are by what we can find out about them via some OSINT and how that could be used in an attack. Most people still think hacking is about targeting technology and are not aware of the extent to which people are targeted. JB: Very true. Now let’s shift gears a bit. I notice that you gave a talk about impostor syndrome at SteelCon last year. Do you think women get it more frequently? KC: It’s tough. A lot of people in the industry struggle with it. I’ve had to work on my own issues with imposter syndrome, so that I don’t let it hold me back. Instead, I use it as a motivator. The danger then, of course, is burnout. I think it impacts a lot of people in this industry because cybersecurity is so diverse. It’s impossible to know everything, and we can become desensitised to how much we do know about our own area of expertise. So, you meet someone else and in conversation with them think, “They know so much more than me,” all the while forgetting that they have their own area of expertise, as you have yours. JB: I also think that most people in the industry have a personality trait whereby they want to keep learning and keep challenging themselves — which is great, but it can mean people sometimes feel like there is a lot of stuff they don’t know. There are also some cultural issues, which a lot of people commented about when I did a bit of research on it. We have a tendency in this community to tear people down if they don’t know something or get something wrong. People often say that women get imposter syndrome more frequently, but I don’t agree, to be honest. Studies have implied that in the past, but I think that could be because women are more likely to talk about it than men. From my research and conversations I’ve had with friends and colleagues in the industry, men can struggle with it just as much as women. That sums up why we all need to encourage each other in the industry. As much as there can be a culture of tearing people down, there are also a lot of people who will build others up, be supportive, and be encouraging. We need more of those people. Well said! It’s clear you’ve spoken at a lot of cons. What was your first con speaking experience? How did you prepare? How did you feel? How did the opportunity arise? KC: I think the first con I spoke at was Manchester BSides four years ago. I was speaking at events before that, on panels, and at more corporate events. But I think that was my first community con. I was approached by one of the organizers, which was great and really gave me the encouragement that I needed. I gave the closing keynote and spoke about the psychology of fear and cybersecurity. To be honest, I was really nervous speaking to a technical audience about something that’s so human-focused. The response was great, and I was pleased to find that people were genuinely interested in the human side of cybersecurity. Around that same time, I spoke at SteelCon about how to communicate cybersecurity messages more effectively, and at IRISSCon about gender and age differences in cybersecurity attitudes and behaviours. JB: I start prep for all my talks in the same way, which is to create a spider diagram on paper of all the key points I want to cover. Or sometimes I use a whiteboard or Post-It notes. I then flesh out all of the points before I start on the slides. I used to script my talks and then rehearse them until I had learned them. But as I’ve gotten more experience and more confidence, I no longer do that. I now prefer to think of the talks as more of a conversation I’m having with the audience. I will know the key point I want to make on each slide and overall for the talk. But I don’t script them, and I practice to some extent but without rehearsing so much. Did speaking at cons get easier as you got more experience? KC: Cons have definitely gotten easier as I’ve gotten more experience, more confidence, and more understanding of the fact that even technical audiences are interested in the human side of cybersecurity. JB: That’s very different than what I did. For BSides Toronto, I made a PowerPoint presentation from research notes, then I discussed each slide spontaneously. It was amazing that I kept to the 20-minute time limit. I was co-presenting with my ex-husband, and he was going to go on a tangent on a totally unrelated topic. I had to stop him and redirect the presentation to the subject matter. KC: Everyone has their own style I think, and after a while, they find what works best for them, which is why giving advice to others can be tricky. JB: Definitely. Now on to another gender-related question. In previous blogs, I mentioned that I’ve found I’ve been discriminated against less often in cybersecurity than in my earlier jobs due to my gender. What has your experience been? KC: I’ve found the same, too. I definitely experienced more discrimination when I was just starting out in the industry than I do now. I don’t know if that’s because things are progressing or because we are more likely to face discrimination when we are in more junior positions and less established in the industry. Or maybe it’s because we know the industry better now and know which people, companies, and events to avoid! JB: Yeah, I agree. Sexism is less of a problem, but it’s still there. I’ve been pleased by how many women and transgender people I’ve met in our field, and articles like these help. KC: Very true. JB: I have to say, I find the topic of your talk at BSides London last year interesting. The history of the word “cyber.” I wrote an for Tripwire on the differences, similarities and origins of the concepts of information security, cybersecurity, computer security, etc. recently. I think sometimes people lose sight of the “meta” stuff, the cultural stuff. KC: article Thanks. That’s an example of a talk I’d been thinking about for a year or so before I did it. I felt like I was putting my head above the parapet with that one because a lot of people in the community obviously hate the word “cyber,” which I understand but think we need to move on from. JB: I found that when I was talking to senior executives or people in the media or the general public, they related to “cybersecurity” so much more than “information security.” And although they technically have their own distinct definitions, we often use them interchangeably. So, I wanted to look at the cultural issues around the language we use and encourage people to address the fact that cyber is the word people outside of the industry relate to. I did some research and found that most people in the community refer to what we do as “information security” but most people in the public call it “cybersecurity.” In fact, more people in the public call what we do “e-security” than “information security.” When we’re trying to raise awareness and change behaviours, the language we use really matters. E-security? I’ve never heard of that term. Is it more common in the UK? KC: Not at all! It really surprised me, too, because I have never heard anyone actually use the term. JB: Wow. That’s amazing. I would have thought information security was more common. On another note, what advantages do you believe there are to people who don’t identify as male (women, nonbinary people) being in cybersecurity? How do you think we uniquely benefit the industry? KC: For me, it comes down to talent, representation and fairness. First and foremost, talent is equally distributed among the population; it does not discriminate. So, when groups are discriminated against or not equally represented in an industry, that industry is missing out on the talent that those individuals could provide. We deal with some really complicated issues in cyber security, and we need that talent to address those problems. Having diversity also facilitates the representation of different world views and different experiences. People with different life experiences will come at problems differently. JB: Diversity also breeds diversity, so from a representation point of view, the more diversity we have the more that sends a message that “you can do it too.” From a fairness point of view, this is a really cool industry to work in, and I want people who would be interested in the field and who would contribute to it to know they are welcome regardless of their gender identity or any other factor! That’s an excellent answer. One final question… What do you think the greatest challenges will be in cybersecurity in the coming years? KC: I think we will continue to struggle with the same problems we have for decades, like patching, legacy systems, shadow IT, and of course human behaviour. But with the pace of technological change (or rather, the pace of change in how we use technology) continuing to grow so rapidly, we face the risk of still being challenged with how to keep up. With more connectivity comes more vulnerability, and so, of course, the is a big challenge that will continue to grow. Engaging with the average person, enabling them to understand the security and privacy concerns with, for example, “smart” devices in the home, is a big challenge. Responsibility for security with regards to the Internet of Things is a tricky issue. We need security built-in from the start, but in a global market with no incentive on manufacturers to do this, we are placing too much responsibility on consumers. Responsibility for cybersecurity is not a new issue, like most of the issues we deal with in cybersecurity, but as our use of the internet continues to grow, the challenges will also grow. JB: Internet of Things Excellent! It’s been a pleasure chatting with you. I’ve learned a lot. KC:

Women in Information Security: Dr. Jessica Barker

The world is a much more connected place than it was 20 years ago. With the change came new expectations. Downtimes can cripple businesses. There is an expectation of privacy and security. If we post on Facebook and the post gets lost due to any kind of issue, people will not tolerate it. Data integrity and durability are more critical than ever. As an organization, we must consider multiple technological tenets—security, availability, latency, durability, integrity, reliability, and privacy. We don’t get to choose from this list; we just sort it by importance based on business needs. Business continuity Disaster can come in many flavors, ranging from natural disasters to hardware failures, misconfiguration, and cyberattacks. The problem with cyberattacks is that we risk having our data stolen and wonder if the rest of the data is trustworthy. Maybe the attack was a sleight of hand, and the primary objective was to introduce malicious data that would haunt the organization forever. After the security incident, we need to recover the data and restore the service to the level our customers expect. One of the issues we face is reconstructing the original picture and configuration. We need to understand how all the pieces work together and their interdependency. Data restoration is more than just restoring a highly scalable web service snapshot. Objective At this point, our primary objective should be to ensure that our services are available and reliable by whatever means necessary. In the context of dependency management, we need to have a comprehensive data and dependency catalog, including the relationships between the entities. This provides us with the necessary insight into what exists. We also need regular operations testing and robust disaster recovery through automation and manual runbooks. We need to cultivate a culture of disaster recovery fire drills and identify fallbacks. Maturity Model Like an individual who enters college goes through freshman, sophomore, junior, and senior years before graduating, businesses need to follow a slow, progressive approach. It’s impractical for a company or organization to go from no disaster recovery to a fully-fledged, perfectly fleshed-out plan. The road to success is incremental, and each step builds on the previous step. Maturity models examine an organization’s current state from any specific perspective, such as disaster recovery, and help the organization reach the desired state or capability. As the organization progresses toward the end goal, it goes through various checkpoints, usually called Levels. Most Maturity Models have four levels, starting from Level 1 up to Level 4. Why are we talking about maturity models? One step in such a disaster recovery maturity model requires that the organization understand dependencies among various entities and data objects. Recovery usually requires restoring the data and bringing back critical systems in a specific incremental manner, Implementation Based on the business needs, understanding dependency and its relationship can be somewhere in the middle levels of the maturity models. In a 4-level system, it is most likely in Level 2 or Level 3. The other approach is to split the Dependency Management into the same number of milestones as the number of levels. Suppose we are using a 4-level maturity model. In that case, we can split up dependency management to span all 4 Levels, starting with the most straightforward steps and going all the way to the most complicated, expensive, and involved steps. Going forward, we will only discuss the dependency management aspect of this maturity model. Level 1 - Discovering and Understanding Dependencies For many organizations, this can be the most daunting task. If dependency management was never considered necessary, there might be no institutional knowledge. We will start by discussing technical dependencies and then discuss process dependencies. Regarding technical dependencies, we need to identify the direct dependencies first. If the code is written in JavaScript and runs on a cloud service, then the direct dependencies might be JavaScript, NodeJS, AWS Lambda, etc. If we use npm for package management, the packages listed in the dependency file are direct dependencies. Next, we have transitive dependencies, which are pulled automatically from direct dependencies. In practice, this forms a directed acyclic graph. Another aspect of technical dependencies is the cloud architecture. Let’s take an example of AWS—we might use EC2, S3, API Gateway, CloudFront, ELB, etc. If the cloud resources were deployed using tools like CloudFormation or CDK, then it would be trivial to determine the dependencies. If the resources were created manually, the dependency diagram must be made manually by reading the source code and drawing conclusions. Process dependency falls under the non-technical category and defines how different stakeholders work together to move forward. It can also outline the release process or runbooks to invoke during an incident. Level 2 - Setup Continuous Dependencies Validation Dependencies can change since there are too many cooks in the kitchen. The organization's continuous integration tool should enumerate and track the direct code and library dependencies. Every time the code is pushed, a snapshot of current pinned dependencies should be saved to recreate the specific circumstances or restore to a known good state. Like the Continuous integration concept, the non-technical aspects should have some automation. Alerts should be created on metric, and using tools like PagerDuty, appropriate people should be notified of issues, and proper escalation channels should be created. It should be tested occasionally to avoid the known problem called Dogs Not Barking - a situation when you wonder if you are not getting any alerts because nothing is wrong or the alerting logic is broken. Some dependencies can be validated by using the Scream test. Under proper notification and preparation, turn off specific dependencies and see what fails. You may find a Load Bearing Mac Mini. Collect all of this configuration and manage it through some kind of provisioning tool like Chef and Terraform Level 3 - Fixing dependencies by adding, updating, or removing Once we have all the dependencies figured out, take some time and pat yourself on the back. Now, back on the issue, the work isn’t done. During the quest, you realize that some dependencies are causing more problems than they solve. One approach would be to update the dependencies. For example, if we are using old versions of OpenSSL, updating them to newer versions can solve many of the warnings raised by the build system and even help us pass any security compliance. Sometimes, the specific versions of two separate packages are incompatible. The solution is to find versions that can work together. This involves changing the version and might involve downgrading one or more packages. Sometimes, just removing a package or dependency solves the problem. It could have been a dead dependency with no further need but causing warnings and spamming the application logs. Under some circumstances, we might have to add a dependency to bring harmony. Suppose a transitive dependency is causing the problem, but we cannot update the direct dependency. In that case, explicitly adding the fixed version of the transitive dependency as a direct dependency can be an acceptable solution. Level 4 - Manual and Automated Disaster Recovery Drills This is the highest form of maturity in disaster recovery. We need runbooks that outline the roles and responsibilities of individuals involved. The runbook should also define the interdependencies and criticality of each step. The disaster recovery process should be practiced regularly by simulating a disaster and identifying possible sources of friction that get introduced when the plan is set in motion. The gold standard should be automated disaster recovery under human supervision. Automating the disaster recovery workflow ensures that humans do not make mistakes that go unnoticed. Automating has an additional advantage in that we can now run stress tests and simulation disasters by turning off certain network parts in a controlled manner to validate whether our automated disaster recovery is performing as expected. Conclusion Dependency management plays a critical role in disaster recovery, which is essential after a security incident. By following a structured and methodological approach, organizations can build their understanding progressively and control the dependencies. Each maturity model level builds on the previous one and strengthens the organization's security posture. While it can be easy to write off dependency management as a superfluous technical exercise, it is primarily about creating a comprehensive framework that brings together computer systems, people, and processes to work harmoniously. The systematic approach ensures that when disaster strikes, even in the form of a security breach, we can safely recover the data and be confident in the integrity of the said data. The world is a much more connected place than it was 20 years ago. With the change came new expectations. Downtimes can cripple businesses. There is an expectation of privacy and security. If we post on Facebook and the post gets lost due to any kind of issue, people will not tolerate it. Data integrity and durability are more critical than ever. As an organization, we must consider multiple technological tenets—security, availability, latency, durability, integrity, reliability, and privacy. We don’t get to choose from this list; we just sort it by importance based on business needs. Business continuity Disaster can come in many flavors, ranging from natural disasters to hardware failures, misconfiguration, and cyberattacks. The problem with cyberattacks is that we risk having our data stolen and wonder if the rest of the data is trustworthy. Maybe the attack was a sleight of hand, and the primary objective was to introduce malicious data that would haunt the organization forever. After the security incident, we need to recover the data and restore the service to the level our customers expect. One of the issues we face is reconstructing the original picture and configuration. We need to understand how all the pieces work together and their interdependency. Data restoration is more than just restoring a highly scalable web service snapshot. Objective At this point, our primary objective should be to ensure that our services are available and reliable by whatever means necessary. In the context of dependency management, we need to have a comprehensive data and dependency catalog, including the relationships between the entities. This provides us with the necessary insight into what exists. We also need regular operations testing and robust disaster recovery through automation and manual runbooks. We need to cultivate a culture of disaster recovery fire drills and identify fallbacks. Maturity Model Like an individual who enters college goes through freshman, sophomore, junior, and senior years before graduating, businesses need to follow a slow, progressive approach. It’s impractical for a company or organization to go from no disaster recovery to a fully-fledged, perfectly fleshed-out plan. The road to success is incremental, and each step builds on the previous step. Maturity models examine an organization’s current state from any specific perspective, such as disaster recovery, and help the organization reach the desired state or capability. As the organization progresses toward the end goal, it goes through various checkpoints, usually called Levels. Most Maturity Models have four levels, starting from Level 1 up to Level 4. Why are we talking about maturity models? One step in such a disaster recovery maturity model requires that the organization understand dependencies among various entities and data objects. Recovery usually requires restoring the data and bringing back critical systems in a specific incremental manner, Implementation Based on the business needs, understanding dependency and its relationship can be somewhere in the middle levels of the maturity models. In a 4-level system, it is most likely in Level 2 or Level 3. The other approach is to split the Dependency Management into the same number of milestones as the number of levels. Suppose we are using a 4-level maturity model. In that case, we can split up dependency management to span all 4 Levels, starting with the most straightforward steps and going all the way to the most complicated, expensive, and involved steps. Going forward, we will only discuss the dependency management aspect of this maturity model. Level 1 - Discovering and Understanding Dependencies For many organizations, this can be the most daunting task. If dependency management was never considered necessary, there might be no institutional knowledge. We will start by discussing technical dependencies and then discuss process dependencies. Regarding technical dependencies, we need to identify the direct dependencies first. If the code is written in JavaScript and runs on a cloud service, then the direct dependencies might be JavaScript, NodeJS, AWS Lambda, etc. If we use npm for package management, the packages listed in the dependency file are direct dependencies. Next, we have transitive dependencies, which are pulled automatically from direct dependencies. In practice, this forms a directed acyclic graph. Another aspect of technical dependencies is the cloud architecture. Let’s take an example of AWS—we might use EC2, S3, API Gateway, CloudFront, ELB, etc. If the cloud resources were deployed using tools like CloudFormation or CDK, then it would be trivial to determine the dependencies. If the resources were created manually, the dependency diagram must be made manually by reading the source code and drawing conclusions. Process dependency falls under the non-technical category and defines how different stakeholders work together to move forward. It can also outline the release process or runbooks to invoke during an incident. Level 2 - Setup Continuous Dependencies Validation Dependencies can change since there are too many cooks in the kitchen. The organization's continuous integration tool should enumerate and track the direct code and library dependencies. Every time the code is pushed, a snapshot of current pinned dependencies should be saved to recreate the specific circumstances or restore to a known good state. Like the Continuous integration concept, the non-technical aspects should have some automation. Alerts should be created on metric, and using tools like PagerDuty, appropriate people should be notified of issues, and proper escalation channels should be created. It should be tested occasionally to avoid the known problem called Dogs Not Barking - a situation when you wonder if you are not getting any alerts because nothing is wrong or the alerting logic is broken. Some dependencies can be validated by using the Scream test . Under proper notification and preparation, turn off specific dependencies and see what fails. You may find a Load Bearing Mac Mini . Collect all of this configuration and manage it through some kind of provisioning tool like Chef and Terraform Scream test Scream test Load Bearing Mac Mini Load Bearing Mac Mini Level 3 - Fixing dependencies by adding, updating, or removing Once we have all the dependencies figured out, take some time and pat yourself on the back. Now, back on the issue, the work isn’t done. During the quest, you realize that some dependencies are causing more problems than they solve. One approach would be to update the dependencies. For example, if we are using old versions of OpenSSL, updating them to newer versions can solve many of the warnings raised by the build system and even help us pass any security compliance. Sometimes, the specific versions of two separate packages are incompatible. The solution is to find versions that can work together. This involves changing the version and might involve downgrading one or more packages. Sometimes, just removing a package or dependency solves the problem. It could have been a dead dependency with no further need but causing warnings and spamming the application logs. Under some circumstances, we might have to add a dependency to bring harmony. Suppose a transitive dependency is causing the problem, but we cannot update the direct dependency. In that case, explicitly adding the fixed version of the transitive dependency as a direct dependency can be an acceptable solution. Level 4 - Manual and Automated Disaster Recovery Drills This is the highest form of maturity in disaster recovery. We need runbooks that outline the roles and responsibilities of individuals involved. The runbook should also define the interdependencies and criticality of each step. The disaster recovery process should be practiced regularly by simulating a disaster and identifying possible sources of friction that get introduced when the plan is set in motion. The gold standard should be automated disaster recovery under human supervision. Automating the disaster recovery workflow ensures that humans do not make mistakes that go unnoticed. Automating has an additional advantage in that we can now run stress tests and simulation disasters by turning off certain network parts in a controlled manner to validate whether our automated disaster recovery is performing as expected. Conclusion Dependency management plays a critical role in disaster recovery, which is essential after a security incident. By following a structured and methodological approach, organizations can build their understanding progressively and control the dependencies. Each maturity model level builds on the previous one and strengthens the organization's security posture. While it can be easy to write off dependency management as a superfluous technical exercise, it is primarily about creating a comprehensive framework that brings together computer systems, people, and processes to work harmoniously. The systematic approach ensures that when disaster strikes, even in the form of a security breach, we can safely recover the data and be confident in the integrity of the said data.

Dependency Management is Critical for Disaster Recovery After a Security Incident

Advancing the Detection of Ultralight Vector Dark Matter through Novel Analytical Strategies

Sales Pitch Shake-Up: Part Two—The Pitch Hack So Obvious, You’ll Kick Yourself

The Definitive Guide to Social Media’s Latest AI Updates: From Gimmicky To Genius

Yes, bad mental health days happen even for hackers. I had one last week. And I'll tell you how I turned it around in about 45 minutes. I had been stressed about more than a few things. To name a few... Business has not been great lately.
I hadn't slept great the night before (it happens, even to sleep hackers sometimes).
There are some exciting but intimidating pivots I'm in the midst of making with my business (which involves a lot of work and learning some new things).
And the looming threat of nuclear war (in the part of the world where my little family lives!) Then, my wife made a perfectly understandable, concerned comment while rushing out the door to attend to matters in Sofia, which set me off. So, I dove into work with ferocious intensity. But I was less productive than I wanted to be. My MacBook was dragging a bit (it needed an optimization which it received), a Brazilian guy messaged me who was excited to read my book for men but my e-commerce store was broken because of a really annoying issue with my new hosting company (so I sent him the book for free - and the store is now fixed, by the way), and some new AI toolsI'm experimenting with were frustratingly not delivering the creative vision I had in my head.When my wife came home a few hours later, it was time to deal with one of my least favorite things in the world: customs paperwork for importing supplements. Getting a package of Biohacking goodness in the EU is often like negotiating with a very litigious demon for the release of your soul from purgatory! My wife is great; she handles most of the unpleasant mess of paperwork this entails, but she had a lot of questions to ask me about the package, interrupting what I was trying to do. Standing in front of my laptop (facing way too many open browser tabs), seething at the world, I realized I was about to blow up at my wife and her small barky dog (my little frenemy here in our abode). I had promised her and myself earlier this year that I'd handle my anger better and that blow-up episodes were behind me, along with explaining to her that sometimes, I needed her to stop talking and give me space. So that's what I did, and it was really time to close my laptop. I sat down in the chair where I meditate, slipped on my headphones, put a calming Brain.FM binaural beat on in my headphones, and I just breathed. Slow in the through the nose filling my belly, slow out the mouth. After 10-15 minutes, I returned to my senses. It was time for a little positive self-talk, so I reviewed the last few days; they had been stressful, but actually, I got a lot of important things done, almost all the important things. All things considered, I was doing pretty well as a husband and entrepreneur this week. And there was a lot of reason for optimism about this year (except for the nuclear war concern, which is a good thing I got a stash of "Nuke Pills" - Potassium Iodide). So, I borrowed a bit from Dr. Joe Dispenza's transformative meditation and began future-casting gratitude. In faith, I raised my hands and quietly praised my Creator (in advance) for the beautiful life waiting for me, where my efforts would come to fruition. After about 30 minutes of that, I was back to cool cat Jonathan. Then, it was time to do a coaching call with one of my favorite clients. The client was also struggling with life a bit; I listened attentively, and I think I was able to provide some insight, inspiration, clarity, and out-of-the-box solutions. It ended up being a downright decent day. To summarize, what works when compounding stress and to-dos push you to the boiling point? Know when to get off the damn computer or your "smart" device.
Establish a rule with your loved ones or domestic partners - sometimes, you need silence and privacy.
Have a designated private space for relaxation - go there.
Binaural beats are a game-changer for mood - have some just a few clicks or swipes away at any given time.
Take 5-10 minutes just to breathe - I know it's boring, but it works!
Positive self-talk - praise yourself for what you've done right recently.
Then, future-cast gratitude - be thankful for the life you'll have. Hopefully, you can borrow from my tool kit when you inevitably find yourself on the verge of a blow-up, meltdown, or panic attack. Yes, bad mental health days happen even for hackers. I had one last week. And I'll tell you how I turned it around in about 45 minutes. I had been stressed about more than a few things. To name a few... Business has not been great lately. I hadn't slept great the night before (it happens, even to sleep hackers sometimes). There are some exciting but intimidating pivots I'm in the midst of making with my business (which involves a lot of work and learning some new things). And the looming threat of nuclear war (in the part of the world where my little family lives!) Business has not been great lately. I hadn't slept great the night before (it happens, even to sleep hackers sometimes). There are some exciting but intimidating pivots I'm in the midst of making with my business (which involves a lot of work and learning some new things). And the looming threat of nuclear war (in the part of the world where my little family lives!) Then, my wife made a perfectly understandable, concerned comment while rushing out the door to attend to matters in Sofia, which set me off. So, I dove into work with ferocious intensity. But I was less productive than I wanted to be. My MacBook was dragging a bit (it needed an optimization which it received), a Brazilian guy messaged me who was excited to read my book for men but my e-commerce store was broken because of a really annoying issue with my new hosting company (so I sent him the book for free - and the store is now fixed, by the way ), and some new AI tools I'm experimenting with were frustratingly not delivering the creative vision I had in my head. When my wife came home a few hours later, it was time to deal with one of my least favorite things in the world: customs paperwork for importing supplements. Getting a package of Biohacking goodness in the EU is often like negotiating with a very litigious demon for the release of your soul from purgatory! My wife is great; she handles most of the unpleasant mess of paperwork this entails, but she had a lot of questions to ask me about the package, interrupting what I was trying to do. by the way new AI tools Standing in front of my laptop (facing way too many open browser tabs), seething at the world, I realized I was about to blow up at my wife and her small barky dog ( my little frenemy here in our abode). I had promised her and myself earlier this year that I'd handle my anger better and that blow-up episodes were behind me, along with explaining to her that sometimes, I needed her to stop talking and give me space. So that's what I did, and it was really time to close my laptop. barky my little frenemy I sat down in the chair where I meditate, slipped on my headphones, put a calming Brain.FM binaural beat on in my headphones, and I just breathed. Slow in the through the nose filling my belly, slow out the mouth. After 10-15 minutes, I returned to my senses. It was time for a little positive self-talk, so I reviewed the last few days; they had been stressful, but actually, I got a lot of important things done, almost all the important things. All things considered, I was doing pretty well as a husband and entrepreneur this week. And there was a lot of reason for optimism about this year (except for the nuclear war concern, which is a good thing I got a stash of "Nuke Pills" - Potassium Iodide). So, I borrowed a bit from Dr. Joe Dispenza's transformative meditation and began future-casting gratitude. In faith, I raised my hands and quietly praised my Creator (in advance) for the beautiful life waiting for me, where my efforts would come to fruition. After about 30 minutes of that, I was back to cool cat Jonathan. cool cat Then, it was time to do a coaching call with one of my favorite clients. The client was also struggling with life a bit; I listened attentively, and I think I was able to provide some insight, inspiration, clarity, and out-of-the-box solutions. It ended up being a downright decent day. To summarize, what works when compounding stress and to-dos push you to the boiling point? To summarize, what works when compounding stress and to-dos push you to the boiling point? Know when to get off the damn computer or your "smart" device. Establish a rule with your loved ones or domestic partners - sometimes, you need silence and privacy. Have a designated private space for relaxation - go there. Binaural beats are a game-changer for mood - have some just a few clicks or swipes away at any given time. Take 5-10 minutes just to breathe - I know it's boring, but it works! Positive self-talk - praise yourself for what you've done right recently. Then, future-cast gratitude - be thankful for the life you'll have. Know when to get off the damn computer or your "smart" device. Establish a rule with your loved ones or domestic partners - sometimes, you need silence and privacy. Have a designated private space for relaxation - go there. Binaural beats are a game-changer for mood - have some just a few clicks or swipes away at any given time. Take 5-10 minutes just to breathe - I know it's boring, but it works! Positive self-talk - praise yourself for what you've done right recently. Then, future-cast gratitude - be thankful for the life you'll have. Hopefully, you can borrow from my tool kit when you inevitably find yourself on the verge of a blow-up, meltdown, or panic attack.

7 Lifehacks for Beating Back a Bad "Mental Health Day"

Stories, News & Mentions about BARK

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