The post Can An Arts Centre In Uganda Help Create A Better Music Industry? appeared on BitcoinEthereumNews.com. Music is not just entertainment; it is a tool to address global problems. This is how. The Bidi Bidi refugee camp in Northern Uganda is now the country’s second-largest city, with a population of over 270,000. The camp-turned-city, which was first established in 2016, faces all the challenges of urban life, but these are exacerbated by a lack of infrastructure and the precarious livelihoods of its residents. Yet, it has local government, education, and health infrastructure, a thriving nighttime economy, and the politics and interpersonal challenges that come with living side by side in increasing density. However, one thing that was missing until 2023 was a place to congregate that was free from religious, social, or political bias. This is where the Bidi Bidi Arts and Music Center, which opened its doors that year, came in. The world-class facility offers a space for creation, practice, and performance, led by the Playing for Change Foundation. But it serves a bigger purpose. The building collects rainwater and has a community garden. It is used for maternity care, sexual health seminars, and vaccination drives. Its programming has trained 500 refugees as farmers, who have since provided food for 10,000 people, all despite cuts from the World Food Program. And it is open to everyone, regardless of where they came from, in a place where everyone is adjusting to new personal and structural realities. This is more than an arts centre. It is a replicable model for exploring how to protect, preserve and grow the global music ecosystem at the same time. https://playingforchange.org/support-our-agro-farm-project-in-northern-uganda/ Playing for Change Foundation The traditional music industry is facing headwinds. Technology that has been promoted to serve artists and creatives continues to foster a reality where it is the artists who are serving the technology. The supply of music continues… The post Can An Arts Centre In Uganda Help Create A Better Music Industry? appeared on BitcoinEthereumNews.com. Music is not just entertainment; it is a tool to address global problems. This is how. The Bidi Bidi refugee camp in Northern Uganda is now the country’s second-largest city, with a population of over 270,000. The camp-turned-city, which was first established in 2016, faces all the challenges of urban life, but these are exacerbated by a lack of infrastructure and the precarious livelihoods of its residents. Yet, it has local government, education, and health infrastructure, a thriving nighttime economy, and the politics and interpersonal challenges that come with living side by side in increasing density. However, one thing that was missing until 2023 was a place to congregate that was free from religious, social, or political bias. This is where the Bidi Bidi Arts and Music Center, which opened its doors that year, came in. The world-class facility offers a space for creation, practice, and performance, led by the Playing for Change Foundation. But it serves a bigger purpose. The building collects rainwater and has a community garden. It is used for maternity care, sexual health seminars, and vaccination drives. Its programming has trained 500 refugees as farmers, who have since provided food for 10,000 people, all despite cuts from the World Food Program. And it is open to everyone, regardless of where they came from, in a place where everyone is adjusting to new personal and structural realities. This is more than an arts centre. It is a replicable model for exploring how to protect, preserve and grow the global music ecosystem at the same time. https://playingforchange.org/support-our-agro-farm-project-in-northern-uganda/ Playing for Change Foundation The traditional music industry is facing headwinds. Technology that has been promoted to serve artists and creatives continues to foster a reality where it is the artists who are serving the technology. The supply of music continues…

Can An Arts Centre In Uganda Help Create A Better Music Industry?

Music is not just entertainment; it is a tool to address global problems. This is how.

The Bidi Bidi refugee camp in Northern Uganda is now the country’s second-largest city, with a population of over 270,000. The camp-turned-city, which was first established in 2016, faces all the challenges of urban life, but these are exacerbated by a lack of infrastructure and the precarious livelihoods of its residents. Yet, it has local government, education, and health infrastructure, a thriving nighttime economy, and the politics and interpersonal challenges that come with living side by side in increasing density. However, one thing that was missing until 2023 was a place to congregate that was free from religious, social, or political bias. This is where the Bidi Bidi Arts and Music Center, which opened its doors that year, came in. The world-class facility offers a space for creation, practice, and performance, led by the Playing for Change Foundation. But it serves a bigger purpose. The building collects rainwater and has a community garden. It is used for maternity care, sexual health seminars, and vaccination drives. Its programming has trained 500 refugees as farmers, who have since provided food for 10,000 people, all despite cuts from the World Food Program. And it is open to everyone, regardless of where they came from, in a place where everyone is adjusting to new personal and structural realities.

This is more than an arts centre. It is a replicable model for exploring how to protect, preserve and grow the global music ecosystem at the same time.

https://playingforchange.org/support-our-agro-farm-project-in-northern-uganda/

Playing for Change Foundation

The traditional music industry is facing headwinds. Technology that has been promoted to serve artists and creatives continues to foster a reality where it is the artists who are serving the technology. The supply of music continues to vastly exceed demand. Three-quarters of the music uploaded online is, at present, never listened to. Touring, once a robust revenue source for many, faces financial challenges due to increased costs, higher insurance premiums, and the loss of markets resulting from conflicts or climate change. Yet, at the same time, the industry continues to grow, buoyed by double-digit growth in emerging music markets and an increase in local language music dominating local charts.

When examining Bidi Bidi alongside the challenges facing the global music ecosystem, solutions being trialed in Northern Uganda offer unique insights. Bidi Bidi is, like any other arts centre, a talent incubator. There is a recording studio on site where the next global superstar could emerge. Music lessons teach future practitioners. Performances build talent and develop audiences. But that’s not the sole purpose here. Instead, a different approach is taken that utilizes music for social benefits alongside the writing, recording, and performing. Here, music is intentionally used as a tool to foster community cohesion, address mental health and post-traumatic stress, and create a space for entrepreneurs and independent thinkers. It is an intentional and strategic tool for collective benefit, to solve collective problems.

Still, the Bidi Bidi Music and Arts Center is seen as a nice thing to have; a response to a crisis, a singular example for a singular purpose. It is not, on the surface, connected to global music industry activity. This is incorrect. By doubling down on music’s social benefits, it becomes easier to argue and expand its economic benefits. For example, as the centre has developed, the Ugandan industry has seen improvements in government positions towards copyright and music investment. It may be a start, but it is encouraging.

The trick is to see Bidi Bidi, or any similar centre, like a train line. Without the tracks, no trains can run. Regardless of the trains being brand new, if there are tracks, it is not going anywhere. Music requires tracks as well, but its tracks are investment, infrastructure, copyright and a recognition of music’s impact. Yes, music can move around the world seamlessly, but the economic and social benefits of it, in places where it can deliver the most impact, cannot. Instead, a recording becomes more like a train car without a track.

The Arts Centre is part of the track. And a connected network also means that stations must be built and concessions created, all of which create jobs and skills. With music, the structure is the same. While there is a considerable amount of analysis that goes into the economics of building train tracks, with music, that foresight and analysis—both on social and economic issues—are often absent.

Bidi Bidi is providing a living, breathing example to change this. We can both find the next superstar and train farmers, chefs, and hospitality workers of the future. We can increase access to recording, while also tackling sexual health. And we can do it better, leading with music, because of its impact on everyone, everywhere, and music – and those who make it – will be one of the main beneficiaries of this We just need more Bidi Bidi’s.

Source: https://www.forbes.com/sites/shainshapiro/2025/09/23/can-an-arts-centre-in-uganda-help-create-a-better-music-industry/

Market Opportunity
Harvest Finance Logo
Harvest Finance Price(FARM)
$18,32
$18,32$18,32
+0,16%
USD
Harvest Finance (FARM) Live Price Chart
Disclaimer: The articles reposted on this site are sourced from public platforms and are provided for informational purposes only. They do not necessarily reflect the views of MEXC. All rights remain with the original authors. If you believe any content infringes on third-party rights, please contact service@support.mexc.com for removal. MEXC makes no guarantees regarding the accuracy, completeness, or timeliness of the content and is not responsible for any actions taken based on the information provided. The content does not constitute financial, legal, or other professional advice, nor should it be considered a recommendation or endorsement by MEXC.

You May Also Like

South Korea Launches Innovative Stablecoin Initiative

South Korea Launches Innovative Stablecoin Initiative

The post South Korea Launches Innovative Stablecoin Initiative appeared on BitcoinEthereumNews.com. South Korea has witnessed a pivotal development in its cryptocurrency landscape with BDACS introducing the nation’s first won-backed stablecoin, KRW1, built on the Avalanche network. This stablecoin is anchored by won assets stored at Woori Bank in a 1:1 ratio, ensuring high security. Continue Reading:South Korea Launches Innovative Stablecoin Initiative Source: https://en.bitcoinhaber.net/south-korea-launches-innovative-stablecoin-initiative
Share
BitcoinEthereumNews2025/09/18 17:54
Trump Cancels Tech, AI Trade Negotiations With The UK

Trump Cancels Tech, AI Trade Negotiations With The UK

The US pauses a $41B UK tech and AI deal as trade talks stall, with disputes over food standards, market access, and rules abroad.   The US has frozen a major tech
Share
LiveBitcoinNews2025/12/17 01:00
Summarize Any Stock’s Earnings Call in Seconds Using FMP API

Summarize Any Stock’s Earnings Call in Seconds Using FMP API

Turn lengthy earnings call transcripts into one-page insights using the Financial Modeling Prep APIPhoto by Bich Tran Earnings calls are packed with insights. They tell you how a company performed, what management expects in the future, and what analysts are worried about. The challenge is that these transcripts often stretch across dozens of pages, making it tough to separate the key takeaways from the noise. With the right tools, you don’t need to spend hours reading every line. By combining the Financial Modeling Prep (FMP) API with Groq’s lightning-fast LLMs, you can transform any earnings call into a concise summary in seconds. The FMP API provides reliable access to complete transcripts, while Groq handles the heavy lifting of distilling them into clear, actionable highlights. In this article, we’ll build a Python workflow that brings these two together. You’ll see how to fetch transcripts for any stock, prepare the text, and instantly generate a one-page summary. Whether you’re tracking Apple, NVIDIA, or your favorite growth stock, the process works the same — fast, accurate, and ready whenever you are. Fetching Earnings Transcripts with FMP API The first step is to pull the raw transcript data. FMP makes this simple with dedicated endpoints for earnings calls. If you want the latest transcripts across the market, you can use the stable endpoint /stable/earning-call-transcript-latest. For a specific stock, the v3 endpoint lets you request transcripts by symbol, quarter, and year using the pattern: https://financialmodelingprep.com/api/v3/earning_call_transcript/{symbol}?quarter={q}&year={y}&apikey=YOUR_API_KEY here’s how you can fetch NVIDIA’s transcript for a given quarter: import requestsAPI_KEY = "your_api_key"symbol = "NVDA"quarter = 2year = 2024url = f"https://financialmodelingprep.com/api/v3/earning_call_transcript/{symbol}?quarter={quarter}&year={year}&apikey={API_KEY}"response = requests.get(url)data = response.json()# Inspect the keysprint(data.keys())# Access transcript contentif "content" in data[0]: transcript_text = data[0]["content"] print(transcript_text[:500]) # preview first 500 characters The response typically includes details like the company symbol, quarter, year, and the full transcript text. If you aren’t sure which quarter to query, the “latest transcripts” endpoint is the quickest way to always stay up to date. Cleaning and Preparing Transcript Data Raw transcripts from the API often include long paragraphs, speaker tags, and formatting artifacts. Before sending them to an LLM, it helps to organize the text into a cleaner structure. Most transcripts follow a pattern: prepared remarks from executives first, followed by a Q&A session with analysts. Separating these sections gives better control when prompting the model. In Python, you can parse the transcript and strip out unnecessary characters. A simple way is to split by markers such as “Operator” or “Question-and-Answer.” Once separated, you can create two blocks — Prepared Remarks and Q&A — that will later be summarized independently. This ensures the model handles each section within context and avoids missing important details. Here’s a small example of how you might start preparing the data: import re# Example: using the transcript_text we fetched earliertext = transcript_text# Remove extra spaces and line breaksclean_text = re.sub(r'\s+', ' ', text).strip()# Split sections (this is a heuristic; real-world transcripts vary slightly)if "Question-and-Answer" in clean_text: prepared, qna = clean_text.split("Question-and-Answer", 1)else: prepared, qna = clean_text, ""print("Prepared Remarks Preview:\n", prepared[:500])print("\nQ&A Preview:\n", qna[:500]) With the transcript cleaned and divided, you’re ready to feed it into Groq’s LLM. Chunking may be necessary if the text is very long. A good approach is to break it into segments of a few thousand tokens, summarize each part, and then merge the summaries in a final pass. Summarizing with Groq LLM Now that the transcript is clean and split into Prepared Remarks and Q&A, we’ll use Groq to generate a crisp one-pager. The idea is simple: summarize each section separately (for focus and accuracy), then synthesize a final brief. Prompt design (concise and factual) Use a short, repeatable template that pushes for neutral, investor-ready language: You are an equity research analyst. Summarize the following earnings call sectionfor {symbol} ({quarter} {year}). Be factual and concise.Return:1) TL;DR (3–5 bullets)2) Results vs. guidance (what improved/worsened)3) Forward outlook (specific statements)4) Risks / watch-outs5) Q&A takeaways (if present)Text:<<<{section_text}>>> Python: calling Groq and getting a clean summary Groq provides an OpenAI-compatible API. Set your GROQ_API_KEY and pick a fast, high-quality model (e.g., a Llama-3.1 70B variant). We’ll write a helper to summarize any text block, then run it for both sections and merge. import osimport textwrapimport requestsGROQ_API_KEY = os.environ.get("GROQ_API_KEY") or "your_groq_api_key"GROQ_BASE_URL = "https://api.groq.com/openai/v1" # OpenAI-compatibleMODEL = "llama-3.1-70b" # choose your preferred Groq modeldef call_groq(prompt, temperature=0.2, max_tokens=1200): url = f"{GROQ_BASE_URL}/chat/completions" headers = { "Authorization": f"Bearer {GROQ_API_KEY}", "Content-Type": "application/json", } payload = { "model": MODEL, "messages": [ {"role": "system", "content": "You are a precise, neutral equity research analyst."}, {"role": "user", "content": prompt}, ], "temperature": temperature, "max_tokens": max_tokens, } r = requests.post(url, headers=headers, json=payload, timeout=60) r.raise_for_status() return r.json()["choices"][0]["message"]["content"].strip()def build_prompt(section_text, symbol, quarter, year): template = """ You are an equity research analyst. Summarize the following earnings call section for {symbol} ({quarter} {year}). Be factual and concise. Return: 1) TL;DR (3–5 bullets) 2) Results vs. guidance (what improved/worsened) 3) Forward outlook (specific statements) 4) Risks / watch-outs 5) Q&A takeaways (if present) Text: <<< {section_text} >>> """ return textwrap.dedent(template).format( symbol=symbol, quarter=quarter, year=year, section_text=section_text )def summarize_section(section_text, symbol="NVDA", quarter="Q2", year="2024"): if not section_text or section_text.strip() == "": return "(No content found for this section.)" prompt = build_prompt(section_text, symbol, quarter, year) return call_groq(prompt)# Example usage with the cleaned splits from Section 3prepared_summary = summarize_section(prepared, symbol="NVDA", quarter="Q2", year="2024")qna_summary = summarize_section(qna, symbol="NVDA", quarter="Q2", year="2024")final_one_pager = f"""# {symbol} Earnings One-Pager — {quarter} {year}## Prepared Remarks — Key Points{prepared_summary}## Q&A Highlights{qna_summary}""".strip()print(final_one_pager[:1200]) # preview Tips that keep quality high: Keep temperature low (≈0.2) for factual tone. If a section is extremely long, chunk at ~5–8k tokens, summarize each chunk with the same prompt, then ask the model to merge chunk summaries into one section summary before producing the final one-pager. If you also fetched headline numbers (EPS/revenue, guidance) earlier, prepend them to the prompt as brief context to help the model anchor on the right outcomes. Building the End-to-End Pipeline At this point, we have all the building blocks: the FMP API to fetch transcripts, a cleaning step to structure the data, and Groq LLM to generate concise summaries. The final step is to connect everything into a single workflow that can take any ticker and return a one-page earnings call summary. The flow looks like this: Input a stock ticker (for example, NVDA). Use FMP to fetch the latest transcript. Clean and split the text into Prepared Remarks and Q&A. Send each section to Groq for summarization. Merge the outputs into a neatly formatted earnings one-pager. Here’s how it comes together in Python: def summarize_earnings_call(symbol, quarter, year, api_key, groq_key): # Step 1: Fetch transcript from FMP url = f"https://financialmodelingprep.com/api/v3/earning_call_transcript/{symbol}?quarter={quarter}&year={year}&apikey={api_key}" resp = requests.get(url) resp.raise_for_status() data = resp.json() if not data or "content" not in data[0]: return f"No transcript found for {symbol} {quarter} {year}" text = data[0]["content"] # Step 2: Clean and split clean_text = re.sub(r'\s+', ' ', text).strip() if "Question-and-Answer" in clean_text: prepared, qna = clean_text.split("Question-and-Answer", 1) else: prepared, qna = clean_text, "" # Step 3: Summarize with Groq prepared_summary = summarize_section(prepared, symbol, quarter, year) qna_summary = summarize_section(qna, symbol, quarter, year) # Step 4: Merge into final one-pager return f"""# {symbol} Earnings One-Pager — {quarter} {year}## Prepared Remarks{prepared_summary}## Q&A Highlights{qna_summary}""".strip()# Example runprint(summarize_earnings_call("NVDA", 2, 2024, API_KEY, GROQ_API_KEY)) With this setup, generating a summary becomes as simple as calling one function with a ticker and date. You can run it inside a notebook, integrate it into a research workflow, or even schedule it to trigger after each new earnings release. Free Stock Market API and Financial Statements API... Conclusion Earnings calls no longer need to feel overwhelming. With the Financial Modeling Prep API, you can instantly access any company’s transcript, and with Groq LLM, you can turn that raw text into a sharp, actionable summary in seconds. This pipeline saves hours of reading and ensures you never miss the key results, guidance, or risks hidden in lengthy remarks. Whether you track tech giants like NVIDIA or smaller growth stocks, the process is the same — fast, reliable, and powered by the flexibility of FMP’s data. Summarize Any Stock’s Earnings Call in Seconds Using FMP API was originally published in Coinmonks on Medium, where people are continuing the conversation by highlighting and responding to this story
Share
Medium2025/09/18 14:40