UNITED NATIONS, Reporting by Michelle Nichols (Reuters) - The United Nations Security Council voted on Thursday to extend a long-running peacekeeping mission in Lebanon for another year after a compromise was reached between France and the United States on language about the freedom of movement of U.N. troops. The U.N. Interim Force in Lebanon (UNIFIL) - established in 1978 - patrols Lebanon's southern border with Israel. The mandate for the operation is renewed annually, and its current authorization was due to expire on Thursday. The French-drafted text was adopted with 13 votes in favor and abstentions by Russia and China. A planned Wednesday vote was delayed as France, the United States and the United Arab Emirates argued over language on U.N. freedom of movement. France kept language in the resolution that spells out that peacekeepers should coordinate with the Lebanese government.

But in a compromise with the U.S. and the UAE, France added back in text from last year's council resolution - which it had deleted - that demands all parties allow "announced and unannounced patrols" by U.N. troops. "The ability of the UNIFIL personnel to carry out their responsibilities, independent of any restrictions, is essential," U.S. Ambassador to the United Nations, Linda Thomas-Greenfield, told the council. "And we've had long-standing concerns regarding the actions by some actors to obstruct the mission's freedom of movement," she said. "The resolution adopted today includes language strongly reaffirming UNIFIL's full freedom of movement."

By Alessandra Riemer, Editor at LinkedIn News — Home prices have risen for a fifth consecutive month amid an increasingly tight housing …

by Matt Asay -- infoworld -- By now you’ve used a generative AI (GenAI) tool like ChatGPT to build an application, author a grant proposal, or write all those employee reviews you’d been putting off. If you’ve done any of these things or simply played around with asking a large language model (LLM) questions, you’ve no doubt been impressed by just how well GenAI tools can mimic human output. You’ve also no doubt recognized that they’re not perfect. Indeed, for all their promise, GenAI tools such as ChatGPT or GitHub Copilot still need experienced human input to create the prompts that guide them, as well as to review their results. This won’t change anytime soon. In fact, generative AI is big not so much for all the exam papers, legal briefs, or software applications it may write, but because it has heightened the importance of AI more generally. Once all the hype around GenAI fades—and it will—we’ll be left with increased investments in deep learning and machine learning, which may be GenAI’s biggest contribution to AI.

To the person with a GenAI hammer

It’s hard not to get excited about generative AI. On the software developer side, it promises to remove all sorts of drudgery from our work while enabling us to focus on higher-value coding. Most developers are still just lightly experimenting with GenAI coding tools like AWS CodeWhisperer, but others like Datasette founder Simon Willison have gone deep and discovered “enormous leaps ahead in productivity and in the ambition of the kinds of projects that you take on.” One reason Willison is able to gain so much from GenAI is his experience: He can use tools like GitHub Copilot to generate 80% of what he needs, and he is savvy enough to know where the tool’s output is usable and where he needs to write the remaining 20%. Most lack his level of experience and expertise and may need to be less ambitious with their use of GenAI. We go through a similar hype cycle for each wave of AI, and each time we have to learn to sift realistic hope from overreaching hype. Take machine learning, for example. When machine learning first arrived, data scientists applied it to everything, even when there were far simpler tools. As data scientist Noah Lorang once argued, “There is a very small subset of business problems that are best solved by machine learning; most of them just need good data and an understanding of what it means.” In other words, however cool it might make you look to develop algorithms to find patterns in petabytes of data, simple math or SQL queries are often a smarter approach.

By: Lyle Daly   -- fool.com/the-ascent -- The top 10% of household incomes starts at $191,406, the top 5% at $290,406, and the top 1% at $867,436. Those are the nationwide numbers, but they also vary considerably if you account for other factors, such as age or location. Income is a key part of personal finance, but it's not all that matters. Incomes vary quite a bit throughout the United States. The median income was $69,717 in 2021, but households in the top 10% and above make significantly more. It's interesting to see how much money these households make -- and how your own income compares. Of Dollars and Data released income research earlier this year with the thresholds for the top 10%, 5%, and 1% of household incomes, based on data from the 2019 Survey of Consumer Finances.

The 2019 survey is the most recent that's currently available. Although it's a few years old, the median inflation-adjusted income of the top 25% of households increased by just 2% from 2019 to 2022. So, the income data still provides a fairly accurate idea of how much the richest households make.

Incomes of the top 10%, 5%, and 1%

Here are the household income thresholds for the top 10%, 5%, and 1%:

Top 10%: $191,406

Top 5%: $290,164

Top 1%: $867,436

As you can see, you need an income nearly three times the national median to crack the top 10%. It takes another $100,000 on top of that to make the top 5%. And the 1% is making beaucoup bucks.